{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Benchmarck of statistical forecast models"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This document compares the performance (mean absolute error and speed) of different statistical models compatible with `skforecast.ForecasterStats`:\n",
    "\n",
    "- SARIMAX from `statsmodels`\n",
    "- ARIMA from `aeon`\n",
    "- ARAR from `skforecast`\n",
    "- ETS from `aeon`\n",
    "\n",
    "It also includes an autoregressive model from `skforecast` using Ridge model from `sklearn` as estimator for reference."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "skforecast version: 0.19.0\n",
      "aeon version      : 1.3.0\n"
     ]
    }
   ],
   "source": [
    "# Libraries\n",
    "# ==============================================================================\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import skforecast\n",
    "from skforecast.stats import Sarimax, Arar\n",
    "from skforecast.recursive import ForecasterStats, ForecasterRecursive\n",
    "from skforecast.model_selection import TimeSeriesFold, backtesting_stats, backtesting_forecaster\n",
    "from sklearn.linear_model import Ridge\n",
    "from sklearn.preprocessing import StandardScaler, OneHotEncoder\n",
    "from sklearn.compose import make_column_transformer\n",
    "\n",
    "from skforecast.plot import set_dark_theme\n",
    "from skforecast.datasets import fetch_dataset\n",
    "import aeon\n",
    "from aeon.forecasting.stats import ARIMA, ETS\n",
    "import matplotlib.pyplot as plt\n",
    "import timeit\n",
    "\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\", category=FutureWarning, module=\"sklearn\")\n",
    "print(f\"skforecast version: {skforecast.__version__}\")\n",
    "print(f\"aeon version      : {aeon.__version__}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Fuel consumption dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">╭──────────────────────────────── <span style=\"font-weight: bold\">fuel_consumption</span> ────────────────────────────────╮\n",
       "│ <span style=\"font-weight: bold\">Description:</span>                                                                     │\n",
       "│ Monthly fuel consumption in Spain from 1969-01-01 to 2022-08-01.                 │\n",
       "│                                                                                  │\n",
       "│ <span style=\"font-weight: bold\">Source:</span>                                                                          │\n",
       "│ Obtained from Corporación de Reservas Estratégicas de Productos Petrolíferos and │\n",
       "│ Corporación de Derecho Público tutelada por el Ministerio para la Transición     │\n",
       "│ Ecológica y el Reto Demográfico. https://www.cores.es/es/estadisticas            │\n",
       "│                                                                                  │\n",
       "│ <span style=\"font-weight: bold\">URL:</span>                                                                             │\n",
       "│ https://raw.githubusercontent.com/skforecast/skforecast-                         │\n",
       "│ datasets/main/data/consumos-combustibles-mensual.csv                             │\n",
       "│                                                                                  │\n",
       "│ <span style=\"font-weight: bold\">Shape:</span> 644 rows x 6 columns                                                      │\n",
       "╰──────────────────────────────────────────────────────────────────────────────────╯\n",
       "</pre>\n"
      ],
      "text/plain": [
       "╭──────────────────────────────── \u001b[1mfuel_consumption\u001b[0m ────────────────────────────────╮\n",
       "│ \u001b[1mDescription:\u001b[0m                                                                     │\n",
       "│ Monthly fuel consumption in Spain from 1969-01-01 to 2022-08-01.                 │\n",
       "│                                                                                  │\n",
       "│ \u001b[1mSource:\u001b[0m                                                                          │\n",
       "│ Obtained from Corporación de Reservas Estratégicas de Productos Petrolíferos and │\n",
       "│ Corporación de Derecho Público tutelada por el Ministerio para la Transición     │\n",
       "│ Ecológica y el Reto Demográfico. https://www.cores.es/es/estadisticas            │\n",
       "│                                                                                  │\n",
       "│ \u001b[1mURL:\u001b[0m                                                                             │\n",
       "│ https://raw.githubusercontent.com/skforecast/skforecast-                         │\n",
       "│ datasets/main/data/consumos-combustibles-mensual.csv                             │\n",
       "│                                                                                  │\n",
       "│ \u001b[1mShape:\u001b[0m 644 rows x 6 columns                                                      │\n",
       "╰──────────────────────────────────────────────────────────────────────────────────╯\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>y</th>\n",
       "      <th>month_1</th>\n",
       "      <th>month_2</th>\n",
       "      <th>month_3</th>\n",
       "      <th>month_4</th>\n",
       "      <th>month_5</th>\n",
       "      <th>month_6</th>\n",
       "      <th>month_7</th>\n",
       "      <th>month_8</th>\n",
       "      <th>month_9</th>\n",
       "      <th>month_10</th>\n",
       "      <th>month_11</th>\n",
       "      <th>month_12</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1969-01-01</th>\n",
       "      <td>166875.2129</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1969-02-01</th>\n",
       "      <td>155466.8105</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1969-03-01</th>\n",
       "      <td>184983.6699</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1969-04-01</th>\n",
       "      <td>202319.8164</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1969-05-01</th>\n",
       "      <td>206259.1523</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1989-09-01</th>\n",
       "      <td>687649.2852</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1989-10-01</th>\n",
       "      <td>669889.1602</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1989-11-01</th>\n",
       "      <td>601413.8867</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1989-12-01</th>\n",
       "      <td>663568.1055</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1990-01-01</th>\n",
       "      <td>610241.2461</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>253 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                      y  month_1  month_2  month_3  month_4  month_5  month_6  \\\n",
       "date                                                                            \n",
       "1969-01-01  166875.2129      1.0      0.0      0.0      0.0      0.0      0.0   \n",
       "1969-02-01  155466.8105      0.0      1.0      0.0      0.0      0.0      0.0   \n",
       "1969-03-01  184983.6699      0.0      0.0      1.0      0.0      0.0      0.0   \n",
       "1969-04-01  202319.8164      0.0      0.0      0.0      1.0      0.0      0.0   \n",
       "1969-05-01  206259.1523      0.0      0.0      0.0      0.0      1.0      0.0   \n",
       "...                 ...      ...      ...      ...      ...      ...      ...   \n",
       "1989-09-01  687649.2852      0.0      0.0      0.0      0.0      0.0      0.0   \n",
       "1989-10-01  669889.1602      0.0      0.0      0.0      0.0      0.0      0.0   \n",
       "1989-11-01  601413.8867      0.0      0.0      0.0      0.0      0.0      0.0   \n",
       "1989-12-01  663568.1055      0.0      0.0      0.0      0.0      0.0      0.0   \n",
       "1990-01-01  610241.2461      1.0      0.0      0.0      0.0      0.0      0.0   \n",
       "\n",
       "            month_7  month_8  month_9  month_10  month_11  month_12  \n",
       "date                                                                 \n",
       "1969-01-01      0.0      0.0      0.0       0.0       0.0       0.0  \n",
       "1969-02-01      0.0      0.0      0.0       0.0       0.0       0.0  \n",
       "1969-03-01      0.0      0.0      0.0       0.0       0.0       0.0  \n",
       "1969-04-01      0.0      0.0      0.0       0.0       0.0       0.0  \n",
       "1969-05-01      0.0      0.0      0.0       0.0       0.0       0.0  \n",
       "...             ...      ...      ...       ...       ...       ...  \n",
       "1989-09-01      0.0      0.0      1.0       0.0       0.0       0.0  \n",
       "1989-10-01      0.0      0.0      0.0       1.0       0.0       0.0  \n",
       "1989-11-01      0.0      0.0      0.0       0.0       1.0       0.0  \n",
       "1989-12-01      0.0      0.0      0.0       0.0       0.0       1.0  \n",
       "1990-01-01      0.0      0.0      0.0       0.0       0.0       0.0  \n",
       "\n",
       "[253 rows x 13 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Download data\n",
    "# ==============================================================================\n",
    "data = fetch_dataset(name='fuel_consumption', raw=True)\n",
    "data = data[['Fecha', 'Gasolinas']]\n",
    "data = data.rename(columns={'Fecha': 'date', 'Gasolinas': 'y'})\n",
    "data['date'] = pd.to_datetime(data['date'], format='%Y-%m-%d')\n",
    "data = data.set_index('date')\n",
    "data = data.asfreq('MS')\n",
    "data = data.loc[:'1990-01-01 00:00:00', ['y']]\n",
    "data['month'] = data.index.month\n",
    "data = pd.get_dummies(data, columns=['month'], prefix='month', drop_first=False, dtype=float)\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train dates : 1969-01-01 00:00:00 --- 1980-01-01 00:00:00  (n=133)\n",
      "Test dates  : 1980-02-01 00:00:00 --- 1990-01-01 00:00:00  (n=120)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 700x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Train-test dates\n",
    "# ======================================================================================\n",
    "set_dark_theme()\n",
    "end_train = '1980-01-01 23:59:59'\n",
    "print(\n",
    "    f\"Train dates : {data.index.min()} --- {data.loc[:end_train].index.max()}  \"\n",
    "    f\"(n={len(data.loc[:end_train])})\"\n",
    ")\n",
    "print(\n",
    "    f\"Test dates  : {data.loc[end_train:].index.min()} --- {data.loc[:].index.max()}  \"\n",
    "    f\"(n={len(data.loc[end_train:])})\"\n",
    ")\n",
    "data_train = data.loc[:end_train]\n",
    "data_test  = data.loc[end_train:]\n",
    "\n",
    "# Plot\n",
    "# ======================================================================================\n",
    "fig, ax = plt.subplots(figsize=(7, 3))\n",
    "data_train['y'].plot(ax=ax, label='train')\n",
    "data_test['y'].plot(ax=ax, label='test')\n",
    "ax.set_title('Monthly fuel consumption in Spain')\n",
    "ax.legend();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "a574bd71b56c43c89047d3db4c267bd7",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/10 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Backtesting ForecasterStats with sarimax statsmodels\n",
    "# ==============================================================================\n",
    "cv = TimeSeriesFold(\n",
    "        steps              = 12,\n",
    "        initial_train_size = len(data_train),\n",
    "        refit              = True\n",
    ")\n",
    "forecaster = ForecasterStats(\n",
    "                 estimator=Sarimax(order=(1, 1, 1), seasonal_order=(1, 1, 1, 12), maxiter=500),\n",
    "             )\n",
    "\n",
    "start = timeit.default_timer()\n",
    "metric_sarimax, pred_sarimax = backtesting_stats(\n",
    "    forecaster = forecaster,\n",
    "    y          = data['y'],\n",
    "    cv         = cv,\n",
    "    metric     = 'mean_absolute_error'\n",
    ")\n",
    "stop = timeit.default_timer()\n",
    "elapsed_time_sarimax = stop - start"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "615564000e904ec299f85dae1afbc6bd",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/10 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Backtesting ForecasterStats with sarimax statsmodels with exogenous variables\n",
    "# ==============================================================================\n",
    "cv = TimeSeriesFold(\n",
    "        steps              = 12,\n",
    "        initial_train_size = len(data_train),\n",
    "        refit              = True\n",
    ")\n",
    "forecaster = ForecasterStats(\n",
    "                 estimator=Sarimax(order=(1, 1, 1), seasonal_order=(1, 1, 1, 12), maxiter=500),\n",
    "             )\n",
    "\n",
    "start = timeit.default_timer()\n",
    "metric_sarimax_exog, pred_sarimax_exog = backtesting_stats(\n",
    "    forecaster = forecaster,\n",
    "    y          = data['y'],\n",
    "    exog       = data.drop(columns='y'),\n",
    "    cv         = cv,\n",
    "    metric     = 'mean_absolute_error'\n",
    ")\n",
    "stop = timeit.default_timer()\n",
    "elapsed_time_sarimax_exog = stop - start"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "49064cae0fac45d2b72bcce1d960ca67",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/10 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Backtesting ForecasterStats with ARIMA aeon\n",
    "# ==============================================================================\n",
    "cv = TimeSeriesFold(\n",
    "        steps              = 12,\n",
    "        initial_train_size = len(data_train),\n",
    "        refit              = True\n",
    ")\n",
    "forecaster = ForecasterStats(\n",
    "                 estimator=ARIMA(p=13, d=1, q=13, iterations=1000),\n",
    "             )\n",
    "\n",
    "start = timeit.default_timer()\n",
    "metric_arima, pred_arima = backtesting_stats(\n",
    "    forecaster = forecaster,\n",
    "    y          = data['y'],\n",
    "    cv         = cv,\n",
    "    metric     = 'mean_absolute_error'\n",
    ")\n",
    "stop = timeit.default_timer()\n",
    "elapsed_time_arima = stop - start"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "713546203c0f4029bcc7a65635f90f5d",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Backtesting ForecasterStats with ARAR skforecast\n",
    "# ==============================================================================\n",
    "cv = TimeSeriesFold(\n",
    "        steps              = 12,\n",
    "        initial_train_size = len(data_train),\n",
    "        refit              = True\n",
    ")\n",
    "forecaster = ForecasterStats(\n",
    "                 estimator=Arar(max_ar_depth=10, max_lag=10)\n",
    "             )\n",
    "\n",
    "start = timeit.default_timer()\n",
    "metric_arar, pred_arar = backtesting_stats(\n",
    "    forecaster = forecaster,\n",
    "    y          = data['y'],\n",
    "    cv         = cv,\n",
    "    metric     = 'mean_absolute_error'\n",
    ")\n",
    "stop = timeit.default_timer()\n",
    "elapsed_time_arar = stop - start"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "ecae6d947a994795a16ab0c0dbfdd9e1",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/10 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Backtesting ForecasterStats with ETS aeon\n",
    "# ==============================================================================\n",
    "cv = TimeSeriesFold(\n",
    "        steps              = 12,\n",
    "        initial_train_size = len(data_train),\n",
    "        refit              = True,\n",
    "        fixed_train_size   = False,\n",
    ")\n",
    "forecaster = ForecasterStats(\n",
    "                 estimator=ETS(seasonal_period=12),\n",
    "             )\n",
    "\n",
    "start = timeit.default_timer()\n",
    "metric_ets, pred_ets = backtesting_stats(\n",
    "    forecaster = forecaster,\n",
    "    y          = data['y'],\n",
    "    cv         = cv,\n",
    "    metric     = 'mean_absolute_error'\n",
    ")\n",
    "stop = timeit.default_timer()\n",
    "elapsed_time_ets = stop - start"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "1f0c520c987d4a45b2e49b776f2b3101",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/10 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Backtesting ForecasterStats with sklearn Ridge\n",
    "# ==============================================================================\n",
    "params = {'alpha': 0.001}\n",
    "forecaster = ForecasterRecursive(\n",
    "                 estimator     = Ridge(**params, random_state=123),\n",
    "                 lags          = 12,\n",
    "                 transformer_y = StandardScaler(),\n",
    "             )\n",
    "\n",
    "start = timeit.default_timer()\n",
    "metric_ridge, predictions_ridge = backtesting_forecaster(\n",
    "    forecaster = forecaster,\n",
    "    y          = data['y'],\n",
    "    exog       = data.drop(columns=['y']),\n",
    "    cv         = cv,\n",
    "    metric     = 'mean_absolute_error'\n",
    ")\n",
    "stop = timeit.default_timer()\n",
    "elapsed_time_ridge = stop - start"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Model</th>\n",
       "      <th>MAE</th>\n",
       "      <th>Elapsed Time (s)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Sarimax Exogenous</td>\n",
       "      <td>20528.190746</td>\n",
       "      <td>4.894212</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Sarimax</td>\n",
       "      <td>20528.190773</td>\n",
       "      <td>1.851720</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Ridge sklearn</td>\n",
       "      <td>22846.649242</td>\n",
       "      <td>0.068417</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ARAR skforecast</td>\n",
       "      <td>24211.988300</td>\n",
       "      <td>0.092543</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ARIMA aeon</td>\n",
       "      <td>33398.995574</td>\n",
       "      <td>0.550011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>ETS aeon</td>\n",
       "      <td>70773.251667</td>\n",
       "      <td>5.297408</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               Model           MAE  Elapsed Time (s)\n",
       "0  Sarimax Exogenous  20528.190746          4.894212\n",
       "1            Sarimax  20528.190773          1.851720\n",
       "2      Ridge sklearn  22846.649242          0.068417\n",
       "3    ARAR skforecast  24211.988300          0.092543\n",
       "4         ARIMA aeon  33398.995574          0.550011\n",
       "5           ETS aeon  70773.251667          5.297408"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Results\n",
    "# ==============================================================================\n",
    "results = pd.DataFrame(\n",
    "    {\n",
    "        \"Model\": [\n",
    "            \"Sarimax\",\n",
    "            \"Sarimax Exogenous\",\n",
    "            \"ARIMA aeon\",\n",
    "            \"ARAR skforecast\",\n",
    "            \"ETS aeon\",\n",
    "            \"Ridge sklearn\",\n",
    "        ],\n",
    "        \"MAE\": [\n",
    "            metric_sarimax.at[0, \"mean_absolute_error\"],\n",
    "            metric_sarimax_exog.at[0, \"mean_absolute_error\"],\n",
    "            metric_arima.at[0, \"mean_absolute_error\"],\n",
    "            metric_arar.at[0, \"mean_absolute_error\"],\n",
    "            metric_ets.at[0, \"mean_absolute_error\"],\n",
    "            metric_ridge.at[0, \"mean_absolute_error\"],\n",
    "        ],\n",
    "        \"Elapsed Time (s)\": [\n",
    "            elapsed_time_sarimax,\n",
    "            elapsed_time_sarimax_exog,\n",
    "            elapsed_time_arima,\n",
    "            elapsed_time_arar,\n",
    "            elapsed_time_ets,\n",
    "            elapsed_time_ridge,\n",
    "        ],\n",
    "    }\n",
    ")\n",
    "results = results.sort_values(by=\"MAE\").reset_index(drop=True)\n",
    "results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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nnzmU7VMaFqeH2wCpVUY7jkRjjun6UNxhqvvEklWeLJ6hQA/3NNpE0LlnLbOxUQIadicXh5ps3LKr1neD+in+19FmRUzXJCEuhr0GrjGB45EeOuoK2KT+PxhS78F+Z2J5HX09FjTHPeqXlX8xt61pj07EiKEnYMXqf9hDUF2CntO8cAHMCRm6uTz36AScedog9oRPflENpR2ymE3sNb+wttWQIKtlwFeuLsFaE69q8RMlqdF9D9zgahKwIlIQ2ZEg0TNvwQrmd0aihS7k5AdNfsUzZs2v5kvYXMTFWoJCOHCjqwu6KTUVEgjWsvKQLBV0k7SWlsPjre3XSZZJstAmxis3zKqU1vP7eFVrpljl9yFL98GsXCZ6yPWG/sn6Sv51ZPGu60GnsZTVIaYDltW6pinTfdBq6j42C4qsdX+vRr1bzI1/qAsQHTzP6o6gD5x/5IMZ+n73sQfcY8GxPJfpPCbLXMANgQTrXTdfxtwTnntkQrVh+ACF9ex72l/kakLXKVouPcxSTnN64Nu++wDz7y4qKYNXPZbp/CI/3tC3O/RjuiEBXCu48v05IQtgsrgOGTUeoZJfWHtfxaluReQKVV/AW9VrTOB4pAfCuiioYx0NXXuOhaW3Je9R9CAw6toH8dDEa9gIQsBSTt+//7/vWlUquv8aXABzQoaCZB6/90a8+PgdSEtJxGszGg4cC1jkKFCuLkg4NiQoWiMU5EYCmILeSAAHgt9mzTs27g8Ba5ymDmEQuBnUJewpsGL8g88fkz7UtQ4S2uT+cSQRTAFpFEhFYqKmTzU9ZJC1mvz5jnYfUW5T+ifrEw1PUvAJ+ezR0PIZl94ZDECheeval/Xd1I4XVbM9VPs+UTk3bOV1i6VQCJw/yfWsI1lND3Y062it0BAypWckkUiWOhrS/nnZ6mrzJCbEshGSmlBwUtXrFAU8kfj9cv6vuH/KG7XmbegB83hx2fjHmnV9Mmr7o9rUa0yoeYMDx2NSfH3HfN3f17ksdd3k63s8Upg11z2KgpMnPvISuwZSkNzwIQNw09UX4tlHbmOjAHO/X3JUy+c0De4DzGnUxeinX/9AWmoSs4ZSdoiGoCAVoq70UFW/p4CpoyFgmas6VHm8IMvQ3xu24bwzh7IgDwp+I2sMXeCOBaVlilUhLbX2UDoF/9SEbgpknaUbN4nO48E/m3eyfRuK/+PWHfuY5fDkE3rXmnbyCX1YH4/2964K+biS4Jn4fy+yTBQd26Whe5f2wem0b+hhrSa0Pc1VepqoK/KdrE/UBxJx5Bva1OOZzkUabqfh+brSNp164rE5z1oz5apLSl1p9ura9+T6QMcFuUIERFbHtmnBh8lQlvFfYf3mneyVskOEejzuY8djPEslWJP67gd18c+/O4JBpEfCr543UiPuA811j6p6btOy3vl0Hu54dDr77rwzTj4my+Y0Hi6AOY3ipXdm4eb7p+KaO6bU8oOsyd8btzFhSJaZqgESBH2mnLpUDY0E5dEQiARPT01Cc/DZ1wtZINSHr0xSg98aTn3WGKhMKQ2lU2AUDe8GIH9BKp9c1wX1k7k/MfFDkdhkpa0JWa/Ix7SpBHKvUk7PunJcVv3ui/m/stdJ99xQrf/0/rF7b2Dvj8baQcFiZOWrCQnruBhliL9qUCZVf6K8ojWHbu+79Qo2/N1cXHrhGejTvboPLlkUyUdz/qLfqqUCa8rxTPudjsXJ999cTTiTxZ1ST7F5vld+m3Dk9hsuCeasrclJA3oxoUJuMOQLXpPx14xmQbsBSCTTfqIHNbL2BggEf1EWjppimUa+/quQryul+Rp15lCWQaIuenRpH/QFJmi/0v6l/Vb1oYTOuZuvDr3EN6WfpN+V4hvquoZVzUBDD7s04tOY86Y57lF9e3YOulrUNSrUWgqR/BfhLhCcRkE5ThtT9vPeya/hi/efZUnMKeMCWSw7t8/AeWcMYcNP9zzx2lGngfn9r01s+PujVydh6e/r4XS6kJlTgHkLluN48NPiP1huUbIgFRWX1mkxairkl0hlXlnRhC/fYCnDLFFGnHnaYBaEQRfTmrz24RcsUptcM845/ST88fe/rJwo+dqSRZQE44tvz6pmZWwMlBWA3F3Iz3Llt++xHJsU7EFDnOR+QBai+598PZgNgYaSR587jCX9p3np9yUrB1mDSOzVjLZuDAaDnpXEJQvT5m17kJmTz3Jq0pAiCaRflq+pZo1//3/fYsQpA/Hxa48zv1FrqY3lLiZRQwEulAasOaAgHur3D0t+R35BMdtvdNMlCyTl0T7a4/n9z77DmacOYvuZihiQPzQ9dFx4zqlsePedT75hN/twhdLnkWilY5hGJPIKi1kWhe6d2uHUk/ox0U/p5wI+m1Wh9IRLvnyTpVIjNxAayaAUZRTDQFkPAlA+VzquJl5/CXp27YAtO/YyMUVly+k8rKtAw3+FOye9jK8+nMoySFAA6j+bd6HMVs6CPmlf0f+F1z3ERmSID/73HTsW6fij4i8UQEs+6FS44q/1W1iasFCg33vS8+8xt7vFX7zB7iE02kHFIwb07srcqS6/9XE2L7kSUL+GnNALb097kAWrkoGAflcauWupexTl+qXUjXQcHjicy0b52rdtg3OGn8hcyj6crWQY4TQ/XABzjnv2CMqVeO+tVzJ3AaomR4FQ3y/6jaVnqss3r7FQsYWMtCRcfO5w3HHDWJY2h/xzj5cApgAvEqmUw/WrH5eGlMi/MTz8zFsskIf8Wm+8chQLliDfu/c++5YJy5qQr+1N90/FpRecwYJm6IYdZTKwAJ7DWXl46d3Z+HbhiqPqE/lZknXtlqsvYssn8VFUbGUW629q5DO9/dHpLPKerEXXXar4SFNBiceefw+ffXV01nK6yVFqJSryMbh/T3Yjrahw4EBmDh557p1aVk6K7qYRCxLvF587jLVftWYj88ej4gbNxYzZ8/Hz8jW4ddxodBp5Gux2J7OSPf/W/4Ki4WiOZzomKcf1bdeNYXlIKTUejSRs23UAU6bPZOdbOHP/k2/grGGDmdglCy1Zz8iySA96tG3/++rnegU+BU1SVgfKFkEilizsJDromK4auEqWuCtufZyNVNA66CGFHlAo6w1lfaHz8b8KBaGdd/X9uPnqC3HBWadg7KjT2UMHBXdS4QgaJaoqMumaeOWEJ9goB12zbrlmNEut98aHXzKXpVAFcCD4eueeg5h4/VicMrgPE6ZUOIbWR+dKVajgDxkn6CGHcpJTH6nvDQng432PIldBnVbLrld9e3Zho3R03NIDGQXBHSl3POf4ISB5EM/CzOE0EioRSn6uw8ZMxP5DR591gBOZKDlYr8Gl4yeFHLnPOTZQaV0qi3vSqFuY+OJwOJyqcB9gDqeRUF168jlc8ecGLn45HA6HwwlDuAsEhxMi119+Pgs2C1Q5evn92S3dJQ6Hw+FwOE2AC2AOJ0TuvOlStElOZEUYKDCCMgxwOBwOh8MJP7gPMIfD4XA4HA7nPwX3AeZwOBwOh8Ph/KfgApjD4XA4HA6H85+CC2AOh8PhcDgczn8KLoCbgCQIiDUa2Wu4tG3JdYdrv1ty3bzfvN/Hu21Lrjtc+92S6+b95v0+3m1but/NDRfATUASRcSZTOw1XNq25LrDtd8tuW7eb97v4922Jdcdrv1uyXXzfvN+H++2Ld3v5oYLYA6Hw+FwOBzOfwougDkcDofD4XA4/ym4AOZwOBwOh8Ph/KfgApjD4XA4HA6H85+CC2AOh8PhcDgczn8KTUt3gMPhcBrDkIE9cergPux91TrulERHr9XA5fFW+z4UjqZtS66b9/vI7QPJlf5YtwV/bdjehLVxOJxIhAtgDocTNlx+4Qh4vT688fE8+Hz+WkJHK0nw+HxNEmRNbduS6+b9Dq29JIkYfc6p7PiZ//OqJqyRw+FEGtwFgsPhhA1t05Lx3aJVtcQvh9MQdLzQcUPHD4fDaRzDLDJ6GZvyqNq64RZgDocTNshy5F2EOc0HP344nMbRQS9j3kABhU4/ev3d/NXajidcAHM4HA6Hw+FwanFWioAXT05DgtML7do8eOTIEcHcBYLD4XA4HA6HU4u+HfRwa0TkRmmRGGEmUy6AORwOh8PhcDg1kJHQRqe8EwS0MUeWZIysreFwOBwOh8PhHDUd9YA1ThHARKolsiRjZG0Nh8PhcDgcDueoOT1aRqalUgDHmyPH/7fRAlgURTx8xzisWTATe9d8gz9/nIH7br2y1nwP3z4OG5Z8xub58v1n0bFdm2rTY6PNeHvag9j5+5fYvmouXplyN0xGQ7V5enbtgO8+fgH7/pqHdYs+xh03jq21ngvPORW/ffcem2fp12/hzNMGNbovHA4nzNHq2L9c5R+N/G9U20Zy2YVnYMuK2dBpqzvQffza43jzuQeO4Y7gcDicY8eQNA3sWin4OS6q8n0k0CiX5jtvuhQ3XD4K9z75GnbuPYT+vbrgtafvha3cjo/m/qjMc+OluPmaC3Hf5NdxKCsP/3fHOMx59xmMGHsHXG4Pm+ftaQ8hJSkOV02cDK1Gg1efuRfTn7wLd056mU03Rxkx971nsOqvjXhk6rvo2aU9Xn3qXpTaKjB73i9snsH9e+Dd5x/G8299hiW/rcUl55/ObijnXnUf61uofeFwOGHOQzODb4/mrA657fPXN2q5Py35A88+chtGjhjC3hMJcTE467TBuPr2JxvfUQ6Hw2kG2qVrsa3KZ4spspwGGrU1g/v3xC8r1mDpqnXIzM7Hgl//xMrVGzGgT9fgPOPHjcYbH36FX1b8he27D+Ceya8hJSke551xMpvepWMGs9Q++PRb2LBlF/7euA1PvPABLj53GJuPGDtqBLRaDR6Y8iZ27T2E+b+sYgJ7wrVjKtdzzWgs//MfvPfZd9izPxPT352Nzdv34qarLgy5LxwOh3O8cbrc+O7n33DlxWcHv7v0ghHIyi3An+s2t2jfOBwOpy7a6WQ44/XVvjOZIysNRKO2Zt2m7bj20nPRqV0a9h3KRq9uHXDSwJ546pWP2PR26SlMYJLlNgBZhzds3oVB/XswITu4Xw9Yy8rx77Y9wXlofr9fxsA+3bBo+RoM6tcDf/2zFR6vNzjPij//wV03X4YYSxSzBNM8H8z6vlr/Vq7egHNHnBxyX2oiCQIk8cjPBFSCs+prY2ipti257nDtd0uum/e77vbkgVbTC01+ebwyTRCgEUV4/f5GFzxoTFuhnvbB1zraz5n3CxbOfhVtkuORm1+MK0afha9/WKpszxHaHqnfTW17tO3Dsd+BEsoEP7daf9uWXPd/vd8jYoBD0WoGCJ8GguSFwaSBroHlHm2/3T4fWq0Afvvjb2CJMuG3799jpSWpvvoLb3+O7xauZNOTE+PYa0GRtVq7gmIrkhOUaUmJcSgqrj6dlmUtswXb0yu5LNRcRqA9CeCkxFgU1lxPkRXJibEh96UmFoMBcSZTyPsj2WIJed7W0rYl1x2u/W7JdfN+V0ev1dS+uPqrXDR9gLapKw21bQMXdxLRdbFrz0E2CnXl6LPx2+qN6N65HW65b2q1bamvbSgcTduWXHdz95uOn8Cxxc+t8Gnbkuv+r/b7rHgJ68yKALZ7UhElZUJjlJAeG3vc1r2/qAitVgCPHnkaxo46nfnqkp9t7+6d8PTD45FXUIyvf1yGcMfmdMLudh9xPrpp0Q+cb7PB08gnlpZq25LrDtd+t+S6eb/rbu/yeOtdbnNZgJvafs63vzC3LHqIX/XXJhzKzguLfre2tkfTno4fOrb4ucX7fTzbRkK/Oyb68adGhF/WoNifhihkQtYBWVbrcet3c9MoATz5/pvw9iffBN0Hduw5iIw2Sbj75suZAM4vLGHfJyXEBt+zz/Gx2LprH3tfUFiChPjqTxBkSY6NtgTb0Cstoyq0jEB75dWKxJrzsPUqP04ofamJT5bha8SPRj9wU032LdW2Jdcdrv1uyXXzfleHpE69ckcVQiSIGi2pjqZtiO2//XklJj9wM64Zey7ufeLVyvlaeb9bXdujaE/zBm7M/NwKn7Ytue7/Yr9TNT74EpTxsHw5DUViHNqSRtIKIS3zaPdZc9Go8SODQc98davi8/shiIo/FrktkDX4tJP6B6dTRoeBfbth/aYd7PO6f3ewNGh9e3YOzkPzi6LAguKI9f/uwJATekOjqXwiGD50AAt2I/eHwDzDqqyHzXPyAPZ9qH3hcDic5oJiEChwuMLuYLEOHA6H0xo5yejB4WglAC5baIcCUXEbdeoE6IQmPbKGvwCmdGP3jL8CZw0bjIy0ZJZNgTIzLFq2OjjPzNk/4N5br8TI009Cjy7tWZ5LEqKBCz6J2GW/r8fLT97NskecOKAnnnt0ArMq03zEdz+vhMfjxStT7kG3zu2Y6wVlfaga9DZzzg8YccoJmHDdGHTpkIEHJ16Nfr264JMvfgq5LxwOh9OcpCYnsJgJt6cywJfD4XBaEyeZ3DikFsDIRwYKC8vZe7tGQmKTgyxaH41ygaB0Zf935zg8P+l2JMTHMDH5+bxFeO2DL4LzvPPpPFbU4qXJdyHaEoW1G7Zh3B1TquXdveuxlzF10kR89cFzzKK8cOmfeOLFGdUsJZQfc9qkiVg05zUUW8vYOgI5gIl1m3bgzsdexiN3XotH774e+w9l4+b7pwZzAIfaFw6HwzneUPaaoYP74pTBffDYtPdaujscDodTLyeYPFirBsDleZLh278ZSAMqtCKSNUD2kUOlIk8A09DdlOkz2X9DTH9vNvuvD0qDFih6UR8UMX3JzY82OA8llQ8klm9qXzgcDud4s/jLNxBjMWPqG59h78Gslu4Oh8Ph1EmqVoY+XoJPFOCUjSjLLoJktbFpflFASpQA2BERRFZWYw6Hw2mFDBml5CrmcDic1sxpFj8OW4zsfR4ygMO74bOVQ/IBPglIMotAgR+RQGTVteNwOBwOh8PhNInh0TIOqQFwigDeCdhtkEj9AognARwhRM6WcDgcDofD4XCO0gKsY+/z/W2ArD2AvQzwKw4DsVGRIxsjZ0s4HA6Hw+FwOE0iWSujY5SA3Cg1B3C+H/C4mAD2yYpV2BQVOZ6zXABzOBwOh8PhHIn2PYGbnwPSuyISGRgFZFp0kAUB5XI0KgIBu14PXH4ugDkcDofD4XD+e/Q/HUhpB/Q4EZGaAeJwdCD/b7ri/6vi8CoCWGuMHNkYOVvC4XA4HA6Hc7xIaa+8miyIRFK1wGFLlQC4TKU6L2HzKm4Roj5yZGPkbAmHw+H8x/lr4UyMHze6xdZPFTmXfPlGi62fwzluaHRAfBvlvdGMSCRFh2AFuLxSA+BQKsARVrcigP3K5Iggcpw5OBwOh9OivPfZd/h4bmU5eg4nYkhuC4hiRFuAE00C9psUoVt4qFL8ss9OJQ2aWytCL8hwyQLCHW4B5nA4nFaEVhOedglJEmF3OFFSqlSN4nAi0v2BMEamADYkKuLX6zXBfXBftWnFavU3KoecpMwW9oTnlZbD4XBUTKLMXskeoRVleGQZyjeh05i2dn/jLB/fzJyGnXsOsveXXnAGvF4fPvt6Iaa/q5RoX7NwJr6avxTtM1Jx7hknY+Gy1bj/yddx0oBemHTP9ejXqwtKrGX4edkaTHvzMzicLtYuIS4Grz51D4YN6Y/8IitefOfzRrsrXHXxOUhMiGXLX/Drn5j80oxgP8dfcxE6d0iH3eHCH2v/xZMvfYiiklI2fejgPpg383ncePczeOD2a9Cja3tcffuTOGVwX5x3xsk458p72XyvPXMfYixR2LBlF1ueTqfFjM/n462PvsKke2/AFRefzbZn+ruz8OX8pcG+PX7vDTjvzKFIS05EflEJvl24Aq/N+ILtO+KL95+FLMtsnURstBm/fv0Wvvz+V0x/T9mvHM5xE8ARagHWmxVJ6JAtEA/vgnK2ASkxgORUFLBdFcCZboQ9XABzOJywpmxI1bKcR1OiM7S2mtXKUGBjuPyiMzH3+yW44NoH0a93F0yffBeycgsw59vFbPqt112M1z/4Aq98MJd9JjE8+92n8OI7s/DAU28wsTv10YmYNmki7p+i+Ni+/ux9SE2Kx9UTJsPhduPZR25DYlxsSP254OxTcOu4i3HHo9Ox70Am4uKi0bNbx+B0rUbCS+/Oxt4DmUiMj8VTD93C1nfdXU9XW84jd1+Hp1/9GAczc1FaVs4EcE1OPbEfcvIKMfbmSThxQE+8+vS9GNy/B9Zu2I6LrnsQF40chhefuBO/rd6InPwi1qa8wsEeAnILitGzS3tMf/JuVNgdePfTb9n0+558DUu/fhu3XHMRZs75ES88cSdy84vw6gxl/3E4x5zUKgJYZwA0WpYeLJLQmJRrW4XPCMFWHBS/K57SYHvZVix3mVGhkZDMLcAcDofDCYXs3EJMmT6Tvd97MAs9u3TAbeMuDgrg1Ws344PPvw9an19+8m58u3AlZs7+gX3efygHk1+cgXkfTcOjU99FemoSzjptMEaNewDbduyDx+fDg0+9hd++fy+k/lD7gqISrPprIwQZOJiVhw1bdgenfzH/1+D7Q1l5eOLFGVg05zWYjAbm5hDg1ffnYtWajQ1aza1lNtaeLLa07XfceCmMBj3e/eQb1u+3Pv4Gd918GU4a2Avzf1nF2rwx86tg+8zsfLz/v+9w8bnDggI4N78Yj017D688fS+SEuJw1mmDMPKqe+HzHc0DEIdTD6IEJGVU/44C4WwliKSRNK+a4aFMDXgjRg0QkbehDVJjXIAF8EoCEg2ICLgA5nA4YU30X2KlG4MkMVHVJBeIJrYNhX82V+bTJNb/uwMTrhsDUQ2q+XfbnmrTe3XviJ5dO2DsqNMr+ygIkCQJbdNT0Ll9OjweL2unUZex50AmrGXVA1fq46clfzAL8OqfPsTK1Rvw629rsfi3v4MCsm/Pznho4jXo1a0jYqKjgv1Mb5OE3fsOB5dTs991sXPvISZ+AxQUWbFzr+ISQvj9fpRYbczSHGD0yNOYdbd9RhtEmQxsu8srVCdElYW//olzRgzB3bdcjkeee4c9JHA4x4WENkoWCJdDqYxmjgVM0RElgFO0gE2rnOflasAbMTwuASs/7AODxQ3hwZ2g2LckM813PK6UzQsXwBwOJ6wJ+OQyESsI8PiFpgngJrY9Fjgcil9vgCijAbO+WYSP5v5Ya96snAImgI+G7LxCDBszEcOH9Mfpp5yAaY/djttvHIuxt0xiQXhz330GK1b/gzsfexnFJWVM+M597xnotJoG+10XAb/dAORl7fV6a30niMrvOKhfd7w97SG8/P4crPjzH9jKK3DxucMx4fox1doYDDr069mZLb9ju7Sj2BscToj+v3kHAYNJEcARlgotVQuU69RMDw7lQTguCvBt7cDeO206aJ0auI1exDEBXP28Dke4AOZwOJzjzMC+3at9PqFvd+w/lM2sn3WxecdedOvUFgcO123V3LM/E1qthgXIkQsEQaKYgsFCxelyY8lva7Hij3/wydyf8Nv895lrBj0NxMdFY9obnzGhTNB6movB/XsiMycfb1Zxg8hok1xrvifuvwl+v4xr73oKn781BUtXrWPBehzOcRXASW0jMhAuVQeUaxUB7LIpvs0XdrYga21icB5NuZYJYItFGxECmKdB43A4nONMemoipjx4CxOpY84bjpuvvpAFb9XHO5/MY0Jw6qMT0Lt7R3Rs1wbnjhjCPhPkS7vs9/UseGxAn67MZeHlKXeHZJElrhh9Fq4ecw66d27HXCrGXjCCtSXhScF5LreH9bFdegpGnn4S7r/tSjQX9GBAPsrk80vBgLdcfRHOO/PkavOcNWwwLh99Nu567BX8tmYj3vvft3jjWSXjBIdzXAWw3RaRqdBStTJsqgXYW+Zgr/3tivU3gLZCsZmaoiIjCo4LYA6HwznOfPPTchj0OiyY9QqmTprIxO+seYvqnX/77gMYO34SOrVPx3cfv4DFX7yBh24fx7IiBLh/yuvIKyjGlzOmYuYrj2HWvF9QWGINqT9ltgpcM3Ykvv/0JSz64nUMGzIAN9z7DMvhSy4PlIHhwnNOw4pv32UBas+8+jGai8Ur/8aHs+ezrBdUVY4yRrz+4ZfB6WSdfnnKPXhjxhfYsmMv++7l9+Yw32J6IOBwjiXMJSqlnfIh7xDgsEWuBVinSEKvtQKJWh0cOxXXIsGg5DzTlisC2GAI/yIYBHeB4HA4nOOMx+tlWSAmTaudpeHkUeNZAF5NNm3dHcxzWxck+G6455lqwXvzFiwPqT+Llq9h//UF/32/6Df2X5W0ARcF369etwXpAy6q1e9X3p/L/gOQkK7JZeMfC643wJBR46vN89zrn7L/qgQyYpBAH3j29dXakx/w+eMeCGnbOZxGEZMIGMgZ1gsUZkWsAE4ySiiUVAFcbMNoSzv4S0XEtLNiv92BeGcb6CqU6ZIhMmynkbEVHA6Hw+FwOMcYOVl1fyjIBPw+wK5mWomwILi4WB17lf0iRJsLaQVK2reidgdQ4ldcq7SqABaUWcMebgHmcDicCOOSUafjpXrcATJzCnDGpdxVgMMJBX/Q/UFN3eeITB9gC8vsAHh9OnR3miC7dLAk2TGnMBeJbgM6MxcINUuEVoBBlOFsZFXM1gYXwBwOh3McoSH/5mbxir+xYfOuet0xOBxOaMg1BbA9Ml0gDEZFzLrcOgxwKllX2g8/hPULZPTzKRZgv00Jfqugcsga4HCYl0PmApjD4XAiDCobTP8cDucYuUDkRq4AFiBDo1OiAITtZuicRuijPNhpyATVsCmDUv3RW6oLCmAqhxzuApj7AHM4HA6Hw+HUwGcwA5Y4cowF8g/VcIGIHB/geA3gUMsgx61VhH2PEZlYtFUZLbJBsQC7ywICWEJSBGRC4wKYw+FwOBwOpwauRLXiYnEeK4FMiUc6pnmggRuQNIDeiIipAqeVIOUaEJ2rgyj50e7UQ1i9S7EK2wRFAHsdGsAtwE4uENrwL4XMBTCHw+FwOBxODdwJGdX8f8+7JAEXXhqLvt7fIyoQLlUHVgRDKtSzz0mdyrD6sBsetdibC17IkvJBpGpwkohEfXgHwBFcAHM4HA6Hw+HUwB2wAOcdQs9+JnTqplh8Y/25EeUHnKqVWREM0aZWeot14pdNVSy8AuDRKX7Akk3JBJGoZo0IZ8J/CzgcDofD4XCOMa4ERQBHl+/D8HNig9+b/JEVCJeqF5kLhKhmedBHu7FyW/V5KkTFDUKvVoOLtoS/EzAXwBwOhxMh/LVwJsaPG31c1/HaM/fh49ceP67r4HBaGllngDc2GQL8OPuEYuj0ItwuP5tmQGQVw0iN0jMXiIAF2AYPHDUyPFjVYhj6CmUeszn8BTBPg8bhcDickHnypRkQhPD3/+NwGkJOUvx/B7iWID1Dw8Tvyl+sOGd0PEyiI6J8gJMNGhzWirCUK6K2XKid36zA40JHVgxDkY1GNW9wOMMFMIfD4bQitBpNqyxWIYoiZFmGrdzOPof/7Y/DaTj/bwJyMFS/in1e9asVudmKMDRKrohygYg3i5AFIWgBtsq1rz+lsrLNoiqAtYbwvwJwAczhcMIao1qXni7HWgnQ+IDGJuhpTNuaQ4NH4puZ07BzjxJFfukFZ8Dr9eGzrxdi+ruz2XdrFs7EV/OXon1GKs4942QsXLYa9z/5Ok4a0AuT7rke/Xp1QYm1DD8vW4Npb34Gh1O5ESXExeDVp+7BsCH9kV9kxYvvfN6oft127cW48uKz2XqtpTYs/m0tnnvtE9gdSrDLFaPPwtMPj8e9T7yGx+65AZ3ap+OU0bfhwYnXIMYShVvun8rm+3rmNOzYfQA+vx+XX3QWPB4PXnxnFr5buBLTJk3EBWefgoIiK554cQaW/7E+KKZfnHwXhp7YF0kJscjOLcCnXy3ER3N+bNzO5XCOE0JqBkbia0iCH/t2ObBtkx1XpylXB73GB1H2wh8hAthiVLZLUgVwvstTa54yQbkuCGWKlVhSr7vhDBfAHA4nrNnzpvYYhjYcuW36xNo3hyNx+UVnYu73S3DBtQ+iX+8umD75LmTlFmDOt4vZ9Fuvuxivf/AFXvlgLvtMonT2u08xIfnAU28wsTv10YlMUN4/5Q02z+vP3ofUpHhcPWEyHG43nn3kNiTGVQbqHAm/LOPJF2cgJ7cQaW2SMO2x2/HE/TfhsWnvBecxGvS486ZL8dAzb6HEakNRcWk923cW3v10Hi649gGMHjkMLzx2B84/cyh+XrYab370FW69dgzeeu4BnHj+zUzAi6KA3PxCTHj4BRRbbRg8oAfbJ/mFJfhxsZpiisNpQQZk5CFRyIXdJWLZzyVI08l4O92PZ/wy/KIAIypQESEuEEadD/AIEJyKJMxy1L7Glau5gGU1UM6tFWASZdj94WsJ5kFwHA6Hc5zJzi3ElOkzsfdgFrOMfjz3J9w27uLg9NVrN+ODz7/Hwcxc9n/3zZfj24UrMXP2D9h/KAfrNu3A5Bdn4LILz4Bep0Wndmk467TBePiZt7Fhyy5s3r4XDz71FoxGJY9nKNCy/1y3GZk5+fhj7b/Mgjz6nNOqzaPTajFp2nts/dT3gPW5Jtt27ccbM79ifX3r42/gcrtRXFLGBD5999oHcxEfF42eXTuw+ckK/toHX+DfbXtwODuP7ZMv5/+Ki2qsn8NpKdKjitnrus16OCr8eL2DHzEawKwmxyUBDFP4B8HpBBmCzh90f5C0PhwurT0OFqgG51MtwEoxDIQ13ALM4XDCmi73eKq4MUjw+HxNdIFoWttQ+Gfzzmqf1/+7AxOuG8NcAQgSglXp1b0jE4tjR51e2UdBgCRJaJuegs7t0+HxeFk7jbqMPQcyYS1To9NDgFwnSGh36ZgBc5SRLZssvvQfELoutwfbdh044rK2766cx+/3M2vxjj2V35ELBJEYHxP87rrLz8flo89CemoSDAYdtFoNtu7cH3L/OZzjiVGjnANlhU6MjpMxNkH53uzxo0wPmCgThCka4U6KVimCEUiBZoxxocRe26prU10gfHYtsxazcsga4GDdz8RhARfAHA4nrAn45NIl2yuBVS9qigBuattjgcNR/S4SZTRg1jeL8NHc2j6xWTkFTAAfDRlpyfjszSfx+dc/45V3Z6OwpBQnDuyFV5++lwnRgAB2ukK7u9UM2pMhw+NVy0hVISD4R587DI/fdyOeefVjZl0utztw+w1jcULfbke1XRzOMUGUYBKVYE/RasObHZX0Z6vKALO7igXYmIZIqAJXTjmA1eA20eQCvLUFsBNe+AXyfVbmrdCKSOYWYA6Hw+E0xMC+3at9PqFvd+w/lM2spXWxecdedOvUFgcO59Q5fc/+TCZUKUBu24597DsSxbHRoQ3J9uvZhfnhPv3KR8yCTJbvC0c2n/vBiQN6Yv2/O/HZVwuDDxwdMlKbbf0cTkMI5mhF4AK4y1CKDD2wxwncv1/EvSf7qwhgMyCIgFz3eRwOpOhEpQpcjqJmvXoSwHXMKAB2yQWz18SsxRVJIhK1dPZyH2AOh8Ph1EN6aiKmPHgLE6ljzhuOm6++EDMbyHjwzifzMLh/T0x9dAJ6d++Iju3a4NwRQ9hngvxxl/2+Hi8+cScG9OmKvj074+Upd9eyJNfHgcPZzL+X+kEuFZSdglwSmgvyC+7bqzNOHzqQ+TM/fMc49O/dtdnWz+E0hCE+BqIgQ5aBiTGKGrxzn4gDrkoLsEVW3HpgjEI408ZsqGYBtkv1p7mpmgqNXCDC3QLMBTCHw+EcZ775aTkMeh0WzHoFUydNZOJ31rxFDfrUjh0/iaUe++7jF7D4izfw0O3jkFugBOYQ9095HXkFxfhyxlTMfOUxzJr3CwpL1JvyESC/3ikvz8QdN16KxV+9iUtGnY7n3/wfmotZ3/yMX5atwXsv/R9+mvUK4mKjmTWYw2kNmBKUkRSjRwZpvP/lC1haKsDqAwyqAI7zFKkzR0dIFTgt+1zqV3x968IaEMA2LVwaEYmhx9y2SrgLBIfD4RxnyEeWskBQRoWanDxqPAvAq8mmrbtx9e1P1rtMCiy74Z5nqgXvzVuwPOQ+fThrPmbOml9v+69+WMr+a0I5ilFl4PPy8Y/V8pseMmp8rXZpAy4Kvnd7vHj46bdw35OvV2v7/FvNJ8I5R0laJ0AfBezfjEjDFGsiuYc4tweFHuDhg4GjXYDfobg7RPsDFuDwzgSRYpRQQC4QgRzAnvpHkQKBcIF546IpGXDrK9oTKtwCzOFwOBwOJ3SS2gLjHgeueCBiqqFVxcSEHWBx+/BStoSiKkFhbnuVIDg2c3hvf6pWUFwgVAtwZgNuVOVqKrRAOWSLObxtqI3q/V8LZ6JtWkqt7z/9cgEee/59lp+S/Nwowpfer/hzA7N4FBZXDstRypvnH78dpw7uhwqHA1//uIxVN/L5Kp3Ihw7ug6ceHI9unduxCkGUX7KmJeLGK0exqOGkhDiWg/KJFz/Axi27g9ND6QuHw+FEIuTS8NITd9Y5LTOnAGdcWvc0DueISBpg9ARAozqARicCdhsiCZNZCgrgXU4Sv8o4hSgLKMqMBU4QoBNVoRjmxTASdT64NSLMqqg9UO6CEF23c69NLYahUS3AUUbxvyOAzx/3ACQ1jQ3Ro0t7fPnBc/hxiVK556mHxuPsYSdiwsMvoqy8glUu+ujVSbj4xkeCKXD+99aTKCgqwegbH0ZyYjzefPZ+Njz4wltKGU8S2J+/NQX/+/pn3PnYyxh2Un+8/OTdzNdt5eoNbJ7RI0/DlAfH49Gp7+Cfzbtw67jRmPPuMxh28UQUlZSG1BcOh8NpDi4b/1izr3Pxir+xYfOukFKWcTiNYthYILld5eeo8PaBrQuTSbH4Rrt9yK1SFO1Cb2/kbWoLQ2o2nENUf/wwL4Zh0XlYXl/RocjBYp8LCczzuX4BHAiY0xvCNwME0Sj5TpV9yO8s8H/28BNZKp/V67bAYjbh6kvOwVOvzGRVhagy0QNT3sCJA3qxlD8ERfxSap+7HnuVJTynuvAvvTsLN15xAbQaZYdef/l5OJSVx/JDUqqfT75cgAW//sHq1ge47boxmPPtL/hy/lLs3ncYjzz3LstbefWYc9j0UPrC4XA4kUqF3cFSqNX1T3mEOZym4E/vSk7rygd7mfIaVVncJFKIMqiZHtx+5HkUkZfmj8Ygf1v2XpNvACQZEjxhHgQnw6hxBwWtIPlYvt/6sEENkFPdJbQ6soy3ROb0Y0OTHThIsF466gx8MOv7YF5JSquz6q9NwXmoMlFmdj4G9e/BKiEN7tcDO/YcrOaGQK4JlMqne+d22LJzHwb164FVf22stq4Vq//B0w/dGlwvrevtj78JTpdlmbUZ1K97yH2pC4kqLVWxcNe77WrASl2BK621bUuuO1z73ZLr5v2uuz3diuqzOVCltOAr5S9qBEfTtiXXzfvduPaBin8EP7ca19av1cN3wa0s7624eZUSENb3NEjmGFZFsLX2uyltY7WKpTPK5YPVL0EnChjl6RWcLqnlgMkP2G6KhqaO5YfDcRIjyXBrlawOhGByQYv627tEL0jzyxVaVizDrRPQ0yRhr0s4Jv12+2oXz2mVAvi8M09GtCUq6JubnBjHymaW2VTHcJWCYiuSE2LZ+6TE2GBJzAABMZyUGAfsVF5rzkOfaV2URigm2gyNRmJuFNWWU2RFlw4ZIfelLiwGA+JMFP0ZGsmWpvv+tFTbllx3uPa7JdfN+10dvVZzxItroDRwUziati25bt7v0KDjJ3Bs8XOrcRScfDHk2CRItmJkrFsI68CzQQ6HUfHJSIiNPW7rPRbtG9OWHqfMklIFTnbJSLREo6MjHm0dccF5NGWKdKJyyL7oWKQ2sP2t+TjpqPOhXOcKZnXwGzxI1jZwfsiAz+mHJIvBXMDPdhTxcG7MMen3/iI1tVxrF8DkbkAuDOSbGynYnE7Y3fUngQ5AN2D6gfNtNpY+qDG0VNuWXHe49rsl1837XXd7l8db73LJGkiCyOv3s1GhxnA0bVty3bzfjWtPxw8dW/zcalx7oesJcPUcyiqeCT/NQE5BLnzF+WxauaSH02qNmGuZrDNALzjYe7ddRnFZBS6p6Ms+b5dy0dOXCkF1GSALcIHWgKw6tj8cjpOOySbYKAVavmIBLoPjiOcHZYKIgZEJ4HKDiGssLjx3sBjbHOJR97u5aZIATm+ThGFD+mP8g88Hv8svLGHZFshSW9XymhQfi3zVoltQaMXAPtVrvSfGK09OBYUlwdekGlZa+kzLdLrc8JWUwev1sewP1ZaTEBtcRih9qQufLMPXiB+NfuCmmuxbqm1Lrjtc+92S6+b9rk6DHmeqECJB1GhJdTRtW3LdvN+Nak/zBm7M/NwKEVECzrlOebtuMbwHtrH3CUIBdDiIHKMlpOWFy/4WTBZIarCX3S5jkKstYmQjrHBgobSdCWA4FBcAo1QB2ZjQ4LJb83GSGEVV4CotwIU+1xHPjzI4FQFs0+JQnBmiUIQn0r24bKd0zH7r5qJJ409XXXw2CotL8euqtcHv/t2+B26PB6ed1D/4HZX9zEhLxvpNO9jndf/uYJkjEuIqzeXDhw5gInXXvkPs8/p/d1RbBpvn5IHs+0AEM63rtJP6VbMGUBuqLR9qXzgcDofD4RyBmETAHAvB64b02zz2lSVGwpXDczEWH8JgDvN6uDUwJlhAruWiX0aRVY+hno7s+yWanUz8eaEIOxKNFn9pWKdBa2PSVasCl+eqvwpcrUwQNg3yjUb4ZGBMPDA4KvRH0e5pwONjRRiVdMvhI4BJbF45+myWv7dq7l5buR1zv1uCpx68BacM7stq07/2zL1Yt2l7MOiM0pjt2ncYb019AL26dWBZIR6581p8+tUCVhmI+N/Xi9A+IxVP3Hcj8+m94YpRuOic0zBj1vzgumZ8/j2uGXsuLr/oTHTpmIEXHr8DJqMBX8z/NeS+cDgcTqRBudrHjxvd0t3gRBJmZURWqiiF4FPu0xecF8vSAYuCH+0M5YgkTHFKWrMojw9ZWV2hg4SDQjG2iDksitKmFoMg0ZjgLwZ0ekDTwkquiaQaJNiMUjALRI6r/iIYNYthMNEs+fF5gRIA92y7Sj14JJ6/XMIdIyVcP6xl06g12gVi+MkDmCX1i++X1Jr21Msz2ZDUh69MUotP/FOt9Kff78f19zzDBOuPn70Mu8PJhPT0d2cH5zmcnYfr7n4aTz80HrdcMxo5eYV46Jm3gjmAiR8W/86syA/fPo4FzW3duQ/j7phSLbvEkfrC4XA4HA4nNAGsqSgFSZzO3QxI6mwMTu4gFWNXE7N5tEZMscq2mQ8Y4bamsveLNNuD6WfIAhonm5gFNDalSjlkW8vFQ0kikBEPtE8S0DkFSIt14Z3F5MPccLsULZDDyiBrq5U6DtUCLMKDZ7M0uCbRg3NigWEWP/YdoT0dKoM6KTtzdGcBHyyVw0cAkxCtWtO9KpR5gSrC0X99UA7K6+56usF1UF7hkVfd1+A8lB+Y/usjlL5wOBxOa4NSPbbGYhVUyIj53DZB6FDmHord4ISxBdhRBlErYNR5ymdyEfCLAhL9RYobQCAvcJhjUqugieuS2OsmKQvZYuW2MZEoKxbQKH9ZZTnkFhDAF54g4NExEtomABqpqjXVBVEU8Oy3DbdP1XixSytBr/oAB6y7DVFZDEMLWfbjUI/T8GH+CtyZKuOpDB+uz2n4+tCtDaDRK33t0CbMLMAcDofTmtBo1Zyw9F4SIItCowOrGtPW62nc0r+ZOQ079xxk7y+94AwmBD/7emFw5GvNwpn4av5S5vp17hknY+Gy1bj/yddx0oBemHTP9ejXqwtKrGX4edkaVjaeiv4QNAr26lP3sIBkCu598R2lmmaoUHGhKy8+m63XWmrD4t/W4rnXPmEjc8QVo8/C0w+Px71PvIbH7rkBndqn45TRt7H1Trr7OvTp3hkarYStO/azEbfNO/YGl5298Uc8OvVdnHnqIJw2pD/e++xbvPL+3Eb1j9PKBLDdhuHDzYBZg3iHF+2LndiQbkasbFWKYUSKAI5Sg7lKFbeG3VJBvRZQPWyVArgFmHC2iI7JyvXP4ZZxqBAoswMndhFw2VDghfkUkFZ/+yS4YfcZYFSrwAW2rSECVmJJFc0dRvTH1z+uxrhOHvROFjC1yI6b5tTffliXStEbnSigJQcPuADmcDhhze0Ppzfr+t6altnoNhSvMPf7Jbjg2gfRr3cXTJ98F7JyCzDn28Vs+q3XXYzXP/gCr3ygiEQSpbPffQovvjMLDzz1BhOdVM592qSJuH/KG2ye15+9D6lJ8bh6wmQ43G48+8htSIw7cj7WAH5ZxpMvzkBObiHS2iRh2mO344n7b8JjVVzFjAY97rzpUuaGVmK1oai4FO3TU/HVD8vwxLYZLHXRLeNG4/O3p+DU0RNYBboAD068mgn2J6d/WC1ehBOeAjjRn41OJ0SxB8SuG4uw16QH0ikXrk0phxwhBQZNRkWN+cu1dYrCqj7AGlGd1kKBcOTyQFzxmhd/7qLRGcColbBmqojEaGBkfwEL/qlfXcZJdggVSt9l0QcHPMznuSEC268rV+abGPcVrn2YbM7K/jodPpz8t4yV9eQbOKOKAKYRhU6JMvaqfsTNzdFlIedwOBzOEcnOLcSU6TOx92AWvlu4Eh/P/Qm3jass77567WZ88Pn3OJiZy/7vvvlyfLtwJWbO/gH7D+Vg3aYdmPziDFx24RkspqFTuzScddpgPPzM29iwZRcr9/7gU2/BaNSH3Cda9p/rNiMzJ5+VjCcL8uhzTqs2D1XUpNgJWj/1nazPNO+3C1dg74FM9v9/z77NhPLQQX2qtf3u599YuXoqbU9inxPOAtiPCztsZSMkvfIr8OSfbpTZFNOiVrQrAjhCiNZ7aXPhtevq9IstUz8zv1kN7QMZMCmBc82J2QAkWBThuPGAIn4JetZc+I8iRq85tX6JpxEAnUAp0JR5XRpX/WU2q1CuPhD4KrQQfDIyXVoccBnx114RQrHyoHtZv/oX1KejOk3t8DkdWs4NgluAORxOWPPe9KxqZW4pB2VTXCCa2jYUamafobSOE64bw/xqiX+37ak2vVf3jujZtQPGjjq9so9Uql2S0DY9haV19Hi8rF2gGhqVe7eWhR6RT64TJLQpk445ysiWTUKW/gNuFhRLsW3XgVq52x+561qWYSchPoaVj6c2lB++Kpu27Q65L5xWjDkWp3p+gxzrh87rx7blVuxzCSgp8yGKpktuwFS9Elg4E6txQLBrIMsiKMt0heCulny8qguELAFa2Q2PqfkfANqrp1thmYyKGp4LP63T4foRbgzvKSAjAcgs1QI9hwBFOUA2hanJSIq2oELnDGaACMX9gbDDDR+UanCuAz7oOmvwZO4ZWLotGX/qPkT7c0Wc3L3utjEmIDFJuV7psvxwZ0gY0l7A+2tbxgeCC2AOhxPWBHxyScQKfhleX+OLKxxN22OBw1H95hNlNGDWN4vw0dwf6wwkJgF8NFAmn8/efBKff/0zXnl3NgpLSnHiwF549el7odVqggLYWUdapDeevQ9xsdF48qUZyM0rgt3pwg+fTWftGtomTngiRlkwRFwCD4CeO0tx216y8gnIt/pAGXLdWl/kWIAFASbRAVEtdewUPfAL1a8INqg+sGXaYDU4D2WBaGbaJyqW04NlBha+VpXsEhG/b5dxWk8BV58iYnre2cBZVysTbSXA7n+QWrwTZaYNEEuU7SjyuXAE7weGLFRWg/vzVw9GdNagGzbhj74P47clFlwHJ9qkCYg1AdYaWSgGqtZeqcyP8kw/dBkSeqTRdy0jgLkLBIfD4RxnBvatbhI5oW937D+UzVJD1gUFlHXr1BYHDufU+qcMEXv2ZzLBSQFyAUgUx0aHdiPu17MLixJ/+pWPmAvFvkPZSEmKD6ntiQN64qM5P2LZ7+uxe99huN0eZgnmRCAaLdpLxfBoZOh8fryxzAG/Ok6eWaq4QLg1AiQzswWHP6Zo6EV70C2gQiLZX52ApVRwSYBbYAK4JXyAA/6/B+MGAB2VUs1V+eJPRVReeaoIKTWjcoIlDjjhLKQOPAVl5socwKX+I6dAq7kP3PkScrPc0Ahe9BHWYnnb8yBZ/Wy06pTutV0bBqvpz7QFMpbsV75LSWk5FwgugDkcDuc4k56aiCkP3sJE6pjzhuPmqy/EzDm1rbsB3vlkHgb374mpj05A7+4d0bFdG5w7Ygj7TJA/LgnQF5+4EwP6dGXFfl6ecnfIVtcDh7OZfy/1g1wqKDvFdZefH1Jb8kkmX2RynaB1vzXtQW7tjVTMsUjz5rG3RsGPXY5KsXLIJkOrBjfGRUeGlBAt0RBFT9C6axfdteZxwcv+2Pw2rSKAW8AHuEOi8nrQkwy06VBr+pJ/gSKbjDaxAs7sqFqI578HfDkd+GcZupfshc1UWQUuVBeIqvNaoMemtUomjH5Yg3VdhkOXrRwT5/QW6s0A4cvz44vdikDXxwnQSdwCzOFwOBHJNz8th0Gvw4JZr2DqpIlM/M6at6je+bfvPoCx4yex1GPfffwCFn/xBh66fRxyCypzjd4/5XXkFRTjyxlTMfOVxzBr3i8oLKksBtQQ5Nc75eWZuOPGS7H4qzdxyajT8fyb/wup7YNPvYmYaDMWzX0drz5zHz6e+2PI6+WEGeY4dBIUH3uTQcaVQysnFXuBaJdiBc4whG49bM0YExRXDkl1gXDUYQFm1eCq+AFH+63MctzctAtYgL1JQJxSsKMqbi/wzRpFjF6TsV35sjAT2LcZ+OVTXLr9W5QZSAA3zge4ar5gi6zHnh0OlNt8iBLKkajdh6ICxRp+eo/q8pLSnfVur/R530E/fsuhTlJCZQHD27aMFZj7AHM4HM5xhtwWKAtEXdUoTx41ngXg1WTT1t24+vYn611mQZEVN9zzTLXgvXkLlofcpw9nzcfMWfPrbf/VD0vZf0227NyHUeMeqBY4+NOvf1abp75iSZwwwxyDJKGQ+f+aRD8mXSJg0SYgn6X8FaB3+ikPGtJ0DmxE+GOKM5EzAPSlyvlYQQF+deTRLYUTcYhi1tNEKods7NFyPsAkgOvxXprzhx8TzpFwlnkbUktLkFuSz75vq5Mx1AJs0jXVAqw88FhkA8iLa/P6cgwdEYMB8iqsdnfDWf6NSEkUWIGOw0VKm66pgNEoAB4Zf+WJaNfVAGehB4Y0ASM6CPjtMJodbgHmcDgcDodTG3MsYiSlwIVR8iPaJODZKxVxmOq3APtIMAIJmtCzj7RmomIooAzQlKouECSA66DSAqxFHLMAN68PsEYE0lXRW58FmNiTC/x1UAdJkHGl9lfAo/T7sgTF5aBUqvQBDgT3hUJg+81Q0i5u2VDBgpGTxVz8FZvKfHyJYT0rLbsnqOnPtEUydvaJxQWXJWKNVdnfA9uiReAWYA6Hw4kwyKXhpSfurHNaZk4Bzri07mmcJqA3ASeeC+xcBxS0gBnreGKOg0FQopU0Lj/LknLhIBEX/qZD/3+Hwr1AgNBjB2JQpuwHV42w/zDDaFGEr6AWwXCIdbhA1EiFZpHLAFFq1u0n8UuVKz0+EdtXPASbZERefxkFbj8KvDKsQjmm2mQU+IA5O9pgSPuDuCpmNd5Uq65dkagI1AqfBL298S4QtiouEITT4ceOLRXoM9CMkngrdDk+eFJEloZtzu/KugZ1Uuyt2gI/PKlGlnBit0uLEXCjfSp3geBwOJyI47LxjzX7Ohev+BsbNu+q1x2Dc4wg4TP2bqBDbyC1A/DNa4gozLEQJEXseMtkzNwCTBwJjBZ7IIckjB+QivXQx5UrqdDCXAAHyiDLqgBmLhB1ELCWsiA4OVAO2dxs2x/IAIEKEdE+O6J9TqSTMZ4Z5Mnv1w6DT8TEvQJ+KuyOZ/z5aGcoxeUnC1i7wY8TzWBhfK5yHbPh+gQ/qwLX6CA4VQATm9aWMwEcpzkIW77I3AuG9xAhCH4muod0VubzFMowdFb2c4GBLOcViA1sTzPDBTCHw+FEGFSSuGpZYs5x4pxrFfFLxFYvBBIRmGPgF8kJVoTXLuONhTKGxMYiZ2PlkLtYpoUmwUH+A0BxLsIZs5FKwAnwO7X1B8GxanCVFmCdoJ5nFAin+tgebzqoglFT6oNdI2J81ztgW7cMSTnb0dMk4OE0P65P9GPaYRGHotPwTfkpuCV6KV67QQPrRTIq9nvxz34Z/jJ9pUW3ERq0XPUBjoIeWlmER/CjuNCLghItkuI8+F1MwenuAsRECeidARwqBDq3UYv+lFbKTtlIJdkBMVpEW5MPe9VnieaC+wBzOBwOh9NIfAPOYPlUg5jjEHGY4+BRC0HYy2W43MDyT7sp09TvpVIt/BqqBhf+xTDitFQaWBFoXvjgErxH9AEWAqnSmrEYRjs1BdpvLhOePDUDGxJi8XN0T/yvQMSUTA3+qNBCJwKTMmQgLgUvWMfis38TYXPIiI0XUD5Ii+QxhuC2ljXC/5eogBulcECEgHO8lQGAebnK/tqaEA9drpKBYnhPEQMCBTBsfmySKq3GkiijsEyRoSM7NH8qNC6AORwOh8NpBI70bvCdPY69T/99Lr7e8hrOte8BtDpEFObYoDSylsro70tHtCMG0HnQ7bRs9r1YqoVb4weimr8YxLEmWkNV4KpkRajHKlrpAqGBn7adcqg0YzGMgAvEfkEHnyigm2YdE7oB3ixSCpPcmCSjg0mEXTbgsW/1uGyKB9F/eKDJ98PuE4MZIMob4f8bqAY3X7uFvR/ib49uvmT2vuCgYsIttEjQ5fiDgXCDAgUw8mVkUom4KhywKiL85BYIhOMCmMPhcDicEJHjUpB/9g2K/+/m3zEtZwEuKVyH+zIXApbQqumFBZKGWTUdsiIT8gu1ON2tVB5cqdmDqLSyoAD2SgJ0IVYhbLVodDAKlVXgGgoKCwhG0S0BHhFaciFoxkwQAReIMjoG6TN2ICqxcv3/OHVYUipAKwKPFSxTvizJx0UWGcY9Pqyf68Z9s+TKHMCNtAATe8VC/CkpAZJjvH2ZP3B+puIOImjLIKkFMYZ0qawKRwFw9njFAmyVlXNln1353D29+f2AuQDmcDgcDicU9CZ4xt4Lv94EIWsPui//CFepEfVJ7jKlzGykYI6F0V8BT8AMui2Dpb0qEMqx0nsQh+3OainDEqJr57IOK8wx0IpkAQ5kRahfFLoFH7yC4h9MItLEqsE1owU4EfD4KU2bss9FQUbvxMxq8zyXqUy7PncVOhXvZQF6l6vpz74qFGAXNE0qglGVX6VdyBHKEAUdLvH0g7XQC7dfy0oj7/HqIVbI0GsFnNJNkZpykQyt+py0HYPYa7agpEJLrTRgNxtcALcCOnc3YNjZMaxSCofD4XBaKf1PBxLaQCovgeb7t/BEmgcejYCFHWMAbXlkWYDNsegpH2RvtYVatClsw94vkrbDJ8jYVqJY+wJlgzOiQs8i0FrLIAuiN+TCEBVV/IBZOWQKAmwGEixAlEFAqbf6A0dvzb8QqpRkXlshYpE7Bhr48fj+b9HDKKNfFOD2A98XC+jU3QhRzXbRVAFM2SO+0WyEGz50lhMxxNsehQ7FF3x1bHzQDYLhlbHXqWE6p1y24JBfGU2w6zQsS4QuvvnlKBfArYDhI+Mw4CQLUtMjzH+Mw+E0K38tnInx40a3dDcil5gE9mLevQ49faW4MkHGT53isKRDLNZmaCBYYhExRMWiMw6xt+bFbSBBxB6xAHukQvbd3zlq9oMKLcuc0MbQNBHVWjDFK8JNo1qAj+QXS9XgAgKYlUPu1E9xiznOdFArwBXTfifsgMNvhFkoQ4d+1TORPK3tz16vtW3CpHTF+vtrKeAxSkhrqz9qCzBRKFZgkUYptXyGpys8u43s/e64aOiyK8voaQtlrNcpGqfAnwb77gL4ZREajR82nwjZxF0g/nOYokSYLVLwPYfD4bQGHpx4NZZ8+UZLd6N1oQY6Sc4KTEr3odCkwZ9pitWtTC8izqwEH0UEllikCfkQyiVIO2MgQ8YS3c7g5H+y3JC0isChwLF4XXin3TPFKcJNWxqaKCxRi0GQy0SKI1PJg9yp73HvZ3tV45Y5FN3gLBewrawje9+nd3UBvjauOxbED4AEGeOSKt0fOvdQthWlTfcBrsp68TC2ibnsIanbYgt7ILLFiNUswOT/u8+s+PvGrojBw3N3wrk/jX3OsraM+wxXXC1McptKq6/BGOY+VBwO56jRanh69laLOsTc05mLS+P9+KlzHGRRsVxV6CQkGytTPIU9UbGIF0oglSr3KLvoQbFYWejBR/lbzc5gKjSLJswFcIzy24XqAlE1FVp8kfpg0Oe0491NtFMtwE6nGghXLmNrljLy0D7ZCXNVX+y4FDzT4dLgR5cf+KFEQJceJiZSNc6mZYGohQD8oNnC0qNZKjTQHjJBq7PD6xagKVJEsC7Pj9JYxd83aZvynbRTDYRT3WiaG36lbWGSUit/eL2BP49wOI1Fq1Uu+HQ70NIQpMiSEjWKxrT1eCqH9ULhm5nTsHOP4kt56QVnwOv14bOvF2L6u7PZd2sWzsRX85eifUYqzj3jZCxcthr3P/k6ThrQC5PuuR79enVBibUMPy9bg2lvfgaHU7lZJcTF4NWn7sGwIf2RX2TFi+983qh+RVui8OT9N+PcM4ZAp9Vi07bdeOrlmdi26wCuGH0WHpx4DZsve+OP7PW+J1/HVz8sZZbhqy4+B4kJsbCW2vDTkj8w+aUZ+E9gUATwg74dOJCgx+akypRO5VoRyQYJOxAhmGMRJZSjTBUn9jqqotk1TmgRxSzAhiQHy6QAb93V01o7JrOGnfyBKnAUBEeFHuqjaiq0GIdaArvrQMBgApz2454BwkEpdzVAvtWP0mIbDvXqgnbCHvTsb0T2ZnXmuBSsj47Hj/YoXGSqwC9WwGsg9wcdRNX664Uf9kZUgasPh+DBQakYvXyp8GXFQexUgb8MepzymwueBAFith9CZw0Ep4iYQuUaps9UNM9hLwnj5q8iyAVwC5OcWtUCzAUwh9NYpt13ebOu7+HpXzS6zeUXnYm53y/BBdc+iH69u2D65LuQlVuAOd8uZtNvve5ivP7BF3jlg7nsM4nh2e8+hRffmYUHnnqDid2pj07EtEkTcf8UxS3h9WfvQ2pSPK6eMBkOtxvPPnIbEuNC90GdMf0ROJ1u3Hj3Mygps+HaS8/HVx9MxWkXT8APv6xCj87tMeLUE3DlhCfY/LZyOy44+xTcOu5i3P7odOzaewhpyQno1qUd/jOYLOhdfhgXSAV4q7NSDW3nFju69zHBI4lI1jXu4ahVY4mFVnRCLIuttyxwnseBDBKBVi1E0aq4AZQqPsLhhskkMnEGNbiMrKINCeDKanBaRGlcQP4hILkd0GMIsHH5cXeBsPkVvZBX7AJK8rAFZ6Ed9qB7PxNytroh08NItGJhvWufgMOJAt7MEdCplxGCIKBknwyaWt7IKnANkS2WMgGMw4o/9VqLBcPznNCUyTgYpWUu0v6DscHVRef6UOYHSqSWiX/iiqsVWYC5AOZwIpPs3EJMmT4Tew9m4buFK/Hx3J9w27iLg9NXr92MDz7/Hgczc9n/3Tdfjm8XrsTM2T9g/6EcrNu0A5NfnIHLLjwDep0Wndql4azTBuPhZ97Ghi27sHn7Xjz41FswhjgET9blAb27YcLDL7C2tI5nXvsYpbZyXHDOqXC63KhwOODz+VBQZGX/9F16ahIKikqw6q+NyM4twKatu4Mi/j+B0YLJB7/F5mQTDsbo4Xb78ftSKwTyB6DrudbeLIFQzUJULCB6gmnB6rIAH6hQraBlWvi1HkUAhymxhsoMEA644RX8MBvqHw8KpEkjC7DeJAKb/1Am9D21WVwgStXjzFZoZyWo96MXKmQzYnNjcIGtBzrqOygNHOXIsjlwz34Re5zk/qD4/5ZuF4+Y7q0pApgwZil9OxxX6RO/3qBcm9xZlYF6Oi8gFesgaGU4/c0fBMctwC2I0STCEl35Exi5AOZwGs1jr39dzY3B4/c12QWiKW3rXaYAlt6H+GdzZfAQsf7fHZhw3RiIonLO/7ttT7Xpvbp3RM+uHTB21OlVlidAkiS0TU9B5/bp8Hi8rJ1GXcaeA5mwlpWH1Lde3TsgymTAlpVzqn1v0OvQIUOxbNYFuTuQBXjNTx9i+Z//4Lc//8HPy9fA66uS7ihS0ejQx52HMYV/48WTlOCdDWtssFf4ITl98EZpEE/ZAMyxQFkRwh5zLLyCL1gZzU4lf2sYuItlNRVaqRYOjRzW5ZDjtA6IedqgdffeUQLuOs+GO2YCCzY07AMsGSRg22rgjCuBjG5AXPJxOQYMWiA1VhXAaqxAeZkHsObD7xewr2wgTv+6CKJTwtWwYPGfO7C6faXGMJhEpLfTQ78hFv12pbPvsgWloMmxIFe0wQ8ZxnIBjjINHFXSYu80KVZeKYtEcaXLhTsrEVJiNvKczf/gyAVwK7H+EnougDmcRhPwyWW3BSrM5GuaAG5q27ogTZqQpIXbHdrSHI7qQShRRgNmfbMIH81V/G+rkpVTwATw0RBlNCKvsASXj3+MCWivn25bCmW2inrbZecVYtiYiczvePjJA/HsoxNw63VjMPaWScy3ObDt/kjUw0YzxhasxR/pFhSatKgo92HDX8oDh+ykUsCARaZiGPHhL4DJuhgVzfIcBKyidslTSwBbhSoWYEGAMc6M8AyFE2CWHMG0YGVwYmR3QCMBky4R8MsmwFvjmGauA9TSK0IWtEB5PnBgi5IOrc+pwJ8/hLhq9b4v+0PPAGEX4NQo7crLfCwiUbAWost8gYlfv9EL0aHBeYs3ILV9FH6URWbR7tLVCMsvaTCuSWRtKXPDr5rqD+dHg0fwwapxIN5rgpRpgr5XGYo0IhK8fhREKwLYkqVcafIEG1JkC/w5cZD6Z2OflY6z5j16uOJqBf6/dCEluAsEhxMZ6PQiswBrdYq1ZmDf7tWmn9C3O/Yfyoa/HqW4ecdedOvUFgcO59T693i92LM/E1qthgXIBSBRHBtiOVpafnJCHLw+H3O5qLr8YqtiEXJ7vEELdVXIFWLJb2vx5EszcNVtT2Bw/57o2UUZbo2O0yIxWcuq6EYcRjMSvUVY0l4peLD+dxs8HuVm7nEo1/AouTzodxnWsKIOMpyyECx0UZcPMAnFgAWYSIoNU/cPYxQMVAZZ3Vay7qYrKZ/RMVnA5UNrD8+ToPSSVZz2lEt1Pdr8u/La5zTIoTjWSlrgtheAG6Y0yv2hSHVLgU+ER33IPvX3LWh7sAQ+jR/W2/Yi+6xi9lAy4GAFbvIMQbLfjHMP9w+K3+XSbnyl2cCq2h1LCnTKQ6E3S1nPLxo96CrnjdNBsGkQVUZhdzJLnUbospR9vsOuZIhoTrjiagUW4MP7lYsIF8AcTmQQEL5qhiykpyZiyoO3MJE65rzhuPnqCzFzTm3rboB3PpnHhOXURyegd/eO6NiuDc4dMYR9JsiXeNnv6/HiE3diQJ+u6NuzM16ecnctS3J9/LZmI3PD+Pi1xzHs5AHISEvG4P498Mhd1wVFdWZ2Ptqlp7D1x8dGQ6fVsOwQV485B907t2PTxowawdaZmZPPfD70emWDNaq/X0RhssBnLmTpzsRSL3b8W2mtctqVBxm94ADMEVAO2RKLOLECdp9Y6QJRhwAupe0lIyZV+HKJ6JUYpsUwomKgoYA/1dpdITqRWqWw2wMXSNDX8VDnFFUrcIUOeoMA7PoHcDmA2CTIGV2PvN7U9kB8KtCmI8vYEGoGiHKHohW8bqW/bfzROGNDHnu/vK8GTpMLuuFZ2HOdC3bJjww5Fnd6hiE6JwayzocfYjdhhWYP5OPgdluoVUaQpEzlYfwzWY/zs3SQtAKQpeTRpnLaB8Ri9t6S6wcp5P2u5s+hzRVXC5KkWoAP7Xf95wSwRiug76AoRKlFQDicSEKnCmCC3n3z03LmX7tg1iuYOmkiE7+z5i2qt/323QcwdvwkdGqfju8+fgGLv3gDD90+DrkFyk2DuH/K68grKMaXM6Zi5iuPYda8X1BYYg25j9fe9TTWrN+K6VPuxqr57+O9F/4PGW2SUFikLGPBr39g+R//4OsPp2HLitkYc/7pzD3imrEjMf/Tl/Dr12/htJP64cZ7n0FJqQ0aixmC6kghShF4LTOaIUqK4PNmeoP+3UR5hZrXlPxCI8ICHItUoRBuhwaCR6xXAJP10KH6c4qlWvROsCEckWJiANEXdIGg/MaiKMDlAbJLZKTFC7huuNhgKjSjSVJSwO34m33nJzeII0HCN/i+U8guEC6X+pu49dDKIi719ge5YG/rkYHfu3fE3z+74JE1iO+8E9vH7EG+oPwuvjg39l+yA+sd2TheFKoW4ChaBXkGpUfhsEXROl41AC5bKGUi2AMfdG4ZYokOMVGU1615icSBqrCAnhZjYjXVLMCSJDDLUWBII5I58/w4ljooObUCSxeUtHR3OJxj6j5J53IQAcxtgbJATJr2Xq35Tx41Hlqp9oMgZVi4+vYn610PZWa44Z5nWNuA7/K8BaGnX6qwO5gbw7OvfFSn7zO5QNz28Au12i1aviawWcF1kx+j1kg3OeVaJgRM35GEyQKBDduKsDur763SCh+S6Q2JREsEWIDNseiKw0HrL2VF8Al135fKBCeMspbN2yYptCDM1oYpjqyVZUF3j6gYxSiVXSLigyVevDBOwN3niZj7hx8VVYzcxbILbVQf6OgoAdZi1Q2i/+nwdz8R/rU/Nbzi1CoCOK2TEkjXAO1VFwiPqhWLnTqc4+2BJNmMMo0PP150ElCRh+IiCQvkcbgIs9C+nwvbnNtgs8UjdqgHW9ce3/utVcNyaEDn1kAq1CMlFShWjX2aLMqb7UOWWAq/IDM/YLJOy1kxkBIK0NxE4GN6eJCYopxo1mIviyL2qr5k/wUrcKduBiZ+idh4/gzGiSx0uurnMPkCRzzmWGiFysjuOlyHwx+jGbKoKA+bo/qPWqRagD0aGVpz+GZCCGKJQ3tkB10CAjlv6yLgBkEWYIPh2KXUak5MsUpqsIAAjklStje3RMS8NcC+PBmJ0QLGn1n9wC6qYgFuE6jAdngXYC2gqHbYO/RpeMWpaqqymtbgIwjgCjUHsH+XCUP87dn77y37YI/SQ45LgTc6EYeF7ljsuRiyLKPXSSbEnOWEbPJh747jG2gmC0COqMQRiJlmkDcUS70mA+ZsRedkCdagJZjw5rTMqEkkXqbCSgAX5CrDSk6KIv4PCGDavhHnVVpIuAtE5NO1lxHnj41HdLgGyDQSfRX3B6Il9O8lo07H7j+/qvN/+bx3ju3KNFpmHdWpUfFVA9sjCckQxQQuUVpFQxhkDdrtbg8px4ByrYQkylUV7kTFIBmFTNQeKVds1UA4CgyLDy0Os1VhitGxDBdChWKQSU5RBbBVYNkfpv+oBIpNHCki1lR3KrRES+Cgl4EtSk7g8i6D6l+pVg8kpiEN+5GMTCClfYM5pGlQpa0SV4YyQZmv3SZFuK+RDmCvcz/g97HlOlMVd4o9RYlYvqjSLaqowIOSouPvapCt5gP2ZimRhJYYDXNz0Dv88KqWXyIglDU5ynY0N9z81sIBcPm5itXE6fDBbJFgiPByyMNHxiLKLKG8zAtztIZtMyeCH3bOjUXXXsodozDfg7W/h6ePYFMEsMYvwysKuPHeJ1Bqa968YItX/I0Nm3fVOY3cMY4lsjkOEuWLZbHeCpHoAZFg1MCuVa7PJQEBLAOXePuhR0EK3MvKUHGJDcmygGz22BPGrmzmWFiEMthsxmpCry5Kq6RCK/eJOKmrhEUbwqsinsksQSTxKwvww4/0NLovi8gpUX7vH9fLuPs8Gb0yBNw+UsTz3yvHehkqBXBcpyr3sp3rgNPGwNmmMzQkaslNqCYp7WEQnBiDj+CFFh9qJ0NOTFcqytVBmzhApxHg9cqwqjmAo0uVdW4SsxTxS5bn+FQ42vVUGpXkYeuGCuj1IoaOiMbmf5rHRSVbFbbaTCMCnuNiphLkliuWB91pAhZgS7YfZS1wukS22gonC7BDtQBTRZkIpUNXPbr3NsHvl/Hzd8XslXwlTVGRu83/Vdp20uOaW1OC4pew/Acedpgrr+r/a1QTh2qq+gM3E+TfW1cKNfqnPMLHCpmsWAYTtKoQCNzDxHr8RcOZJK0Iu5p71aUaRIf42qOHX4neF606lOskJPsqwroiGsMcB4NoD7oE2ERnSC4QNp+IIT1apqxtXZwzJhYnnqc7ohuS2ViZ77hCcKGtGmxGLhAEBTy+NF8RsbecKSI5unY1OHNcFXti/mFWgU3WGSCTZbcu2nREPPIgCX7oBRdMKG8wEC7g/lBmlWHVSxAcIkxu5ZpaKKi5u0uUTBCOtK7VPv+zxob3X87C5vX15/g+HhZgc56fkgNXS4uWJVfmyKZAOEqKpnMpgXDNDVceLQCV6I5RfV8L8gIW4Mh2gaD75LCRMcGT8YQKF2LdygWFW4EjLLvHMC1GXR7PLP3FhR5s2qg85JljW8+N8XgRrY7gaHwys+pErD+sipfK5dL57VVurB7VDViIRAGs8QctwB6XjBS/BSN9PYLTyQJKxQmS3MVKMYxwxhwDUXAHyyCXhWgBtvslnNi5dZj/yeWqU3cjUtpLiE9qaLBbQILJHwz4K4ULbROUbcixVp68SzbLWL/PD6NOwDWnBcoIqxbgcg20naNwxU3J6NCF8tnKEA4rBSbktpXHSDXadEScnB/8aEZpg37AgQwQtjIBbo0IqUhJNVgKZ2Uu3+JcZZ10wyVKKpfva8YkC2WCEzYqoy1XujdospVXCoAL9om5Q6j+wqxCXPMSwZfm1ktMgrLby6zeoPANCuAIdYHoc6qWDTORD9Lfq0rxfHt/pQAOBA9wwp6TR1jQvpdys9nwtw1ffJyH/bFKOd+oRCUHZCRjVPPg+mUNvFRajm6vLWABbg5kQxRkrY6ZxwIBcC6XmgYtnIf/6yFJ64KsmhJlu4hLXP2ggYi9QiH7jipwwS0gyV8c3pkgyIE7Khr+KmWQG/QBVqdJVjoWgA7JPpibv6YBMPJ64JSLgh+T21Q+cKdmNPDwndIOMRIVwVBLC1MOYOW5Djkl1c/d+euU47pPO6F6NTifCMkmIKWNDhddkciEcEfHWiaE/e2qF8Gp7FQHdPIdCH5M9BUomSDqob2aA9hRoeYYz1dG14qEKm4NqsW33s/NhQBkQck2IWdGM/9qs5p5LUt1ewgQKMXsyVErjzQjkam2WjkxScpuz1fdHyLdAkzD4eldNczl4definFxDNDbBMQ6lUdSLoAjh5R05Uaz8mcrfv+1FD6fiPLUvuw7szG8/AIbC7n+yhrl5mSTLPCpgSoR6RBLmJURHdFuZSVjSRq41WBe8qSMtPQXiRp1qN/rx4kl7ZEgRzHr29fajXBBuZaRYIz3WcNbAFMVOEGEW5CDbgEN+QAHguCoJLDgkGCXJYw5sZnvY0ltgUFnA6dfznxvq1ZaPaIA7tgHZpQFt9VvUHIAO9wyrKrYDLBLzWLQvY36oCuQn7+yb+78swSn7C+F4PEzIXzBgEM4GUsgZ3SrHdymMwAJaUiWFYstkeHNBpIylCHiBlwgvB51WQXm6u4PVSzALS6AUZnpwZmVDmd+PDReGfSMWFS1vywQThHEQk7zuw1FntoKA2LUA7lADYCLdAHcvrMyHLN9kx35OW48lqFWTcoyMP8gs4XHYkYKJrP6cJejHttpnVGuT2VvDRovc5GIVOK0VBpV2T67YAy6QLRIGojmgMq4kvuDz85eKZWjT/V7pk0WIqkYhkaHOCg3bsOGGHR1JLFyrvO0m+AQPJVWUJsWFpSFtwuEORYmwQm7W4Ro1xzRAkyZHwKWUPIDpkC4e88X66ycdtyIUdMjEMPGsjy8yW20IQlgTcce0GtKggJYa1EMU5lFtU/enaoAJneEwPYVyMq+ySzR4fIDVjzzVxaGZirBvr396xSxWzXdGeuQ8jkKlYVtUtw5ilBOadegC4TsUwVwkeJSUCjWI4A9LqA89MI4x5pMUVm3PkuH9VmXsPfZBhpFQZ0WYFNW848aRdAVKnyITvxvWYAD21RS6MWFccCAKGBDTjr2fz8AphXJiI6OvG0m+gwyoU2nyNy2uiBfV6MaxEm5rRmd+8EDA9yyPqL9vemazupAkFXIT/XQyIJWqQAizw9YCFp4tWpqMI+ay9yvigaxjuIeYYvJAou/DGKJFsbFbdlXv2v24aBazjVYEaxMiyi5PLyrwZljkCKVwlminLM+0QenauGuj+ADQJkWeXYdq5w2blgzHvSxqgB2q0L9vOuRnFaZWouuO5a6Rho1WqS11TCfdb1VmR4VpwraSm0aJL8MKKmQIYkCuijP9UHr+EN7jbh0p4iNRX5cuF8RfyapHDo6NgJZGQKkdoQGbsjaSiNYtFf1103rXOcmtlP9kh2ysl+lQjWQvqoLRFkRPYmyt0IV/9+WIFt1dYgvKUfX3Yr/Q5ZcuwhHvhoIZ3I1fyW4iLsst3ao0ps5VqgWAPdfEcAuhx+Pq9bfnw+nBR3j4yLQBSImTsKpZ8dg4Fk69v6/gDFKgiAI8PtkOO2qAO6kuD+UIzqiBTAVdfSq7g9OKA6QHkFiQSAEDak2B38tnInx40Y3uf3QwX2QvfFHRFvqD0i5YvRZ2L5qbvCzVjW0edx+pGplaNQawRFlATaaEYUKGDbGQXBLyNPa8Lt2Xy0BSAJYR1kRzGHsAmGOQ7JkhdOqCGCn5DziKEbVTBDbCxXXGKqcFngoPO5EqwJ44wrg31WIEUuh19GIBOAoVFyv2rStozNtu6OtdJC91ZUqD6xxia4qFuDaBNwguqWp7k6q9dssGzC/WMCIrRKu2VLp4pcg5wDtawTCtemAWBRV268GSRlJqSsQLkoPxJnVLBDkWuUDjKqWrOZSQOdeqZrlxdqyAtgpeFFgVPZVj51Z7DXLk1NrPp/gD5Zqbm4i6AoVHiQk0dOmgHKbD44KPyRZwDBvJ5x8sDuNJUWmAFatgr1EH040A2UeEW67csGiYSdLdOS5QAQKfJDwGTws8oO/CLPq/uCyq6rPaAkO9ZX7YiJaACdqZLhUwecRVcuTwwPJE14W4HUbd6D/WdehzBZauiTBX+nWQi4QlN5c8quBcJEU/Gc0wwB7sDBEpsEKuUqmi0CWBAqkkuh9WFuAY5EilMBbqqvm49sQwUwQpVqUOXU4WCAjOUbAjSNCP/DjEjW46IoEpKQ1QTXHqAFUJP5+/hjJ+UpJ4XZ2D86sUIRlWls1M0JVOvRBO+xhb+Vy5bdNaaOMzGYV1T0kvyunuh9wwD0kVq5M+bjYCrQpV5bTxbsXqOkHnFqZAULrU40FOjVGoo5UaBnq5lXYZZTqJJYyTPSDlRyu+fsIqt9v4LUlydIq+15UH4oDfsH1WYubm0ZfllOT4/HW1AewZcVs7F3zDZZ+/Rb69epSbZ6Hbx+HDUs+Y9O/fP9ZdGxH1bIriY024+1pD2Ln718yS8IrU+6GyVg9bLRn1w747uMXsO+veVi36GPccePYWn258JxT8dt377F5qB9nnla76sqR+tLcJKoFMApzPSyNzq2eU3C2rzt62NKgPWSCwRh5AiEg6q+3KGpgxoEEaNUIeWYxMUfeNhtNldvUpacxmPc5kqEsH4TTXhlcQsE0p//8JwZMM0K7NwpRcS1T8ed4ohdkmDQkfJUboht66O1OxJW5IatWNK1qHQ4FrZrkvrnRaCRWJKOgKHS/Qa3sZkYsn0+GGTLcPi1QpmQDEMNF9YeCyQKN4ApmRXAEnmxQMx8sPQF4mIgMW8wxaC9kB7e10H9kARwQYWKpDlqtB68tUMTcHSPFkDNC9OxjQocuRvQmH7nGEqM6yJYWsYIQyYeWso8dyxzoUaZYp9tk1BbAxs4dkSjksuwdXo+yvRlt63eBIHaq2QwCFuBMVbz186ch0a/03S0L0FuVY6SjZ4/iBxyw7BpMrFhFhi+TfexUqjw8ufWCEjwanwpZb6puqFbdH2yllANYA02hPhgAV9OnVty2BlJ5CcTdG9DSZPmVDCmEzSDV+zAVqAjX3DTqChVjicL8T1+C1+vDtXc9hRFj78Qzr36M0rJKH5Q7b7wUN19zIR6d+i4uvO4h2B1OzHn3Geh1lQLg7WkPoXvndrhq4mTccPezGDKoD6Y/eVdwujnKiLnvPYPMnHycd839ePa1T/DghGsw7tJzg/MM7t8D7z7/MOZ+vxgjr7oXi5avwcevPc6W25i+NDdMCPmA6NXJuM1zCtrIlZGPdMHRG4RIC56GXhXAQ7U+UJD42vzk4DTRJUHwSjBGWDEMU42CJkNPj1YsAINHAv1HIBIJWL2DFuBOfdFxXy7O/OsgRKrQudcCc3xL5Ec6vpDuD1h/vX4Rsiwi2qaWCvOKmPnSM3jqwdsw9dEJ2LHqC2xZPhsP3zEu2H7Nwpm4e/wVeOPZ+5lR4CX1WnjSgF7MCEAP72QEePb/boPRUHkTT4iLwadvTMaOP77E6gUzWfnjxkCuDtdffj4+fPUx7F79Ne4df0WdLhDk8rD254+xd/U3+OjVxxAXUzmioVUtn7dceRn+WDIb85fNweOPTMS9N1yPnz56odr6rrlkJFZ++y4zWKz87j1ce/n5CBuMFoiiu7JYglgZv0FQNojANdyhFWAh8xwJnXDEHIc2yA8KYGsjLMDkAyxofPj2bxl7cmXEmwXcNKJx148mjRJVtQBTBohkZRltbW50VAVmYrJyfw1iikbbJGVaGzV2zAMv2rfxN+wCoVqAu6kW4N1iAXaJ+Swl3mhvHwQGBuyFigCODWR6aKe6QaQoo2IZbsWFpmOxE4IsQxYFmKz72XdyjaC59HhlXZ4ypQiGpArgmhkVCGnH32g35xmI2YpluyXJdCuuD0SWWa7XlSYQCNfcNMrUcOdNlyE7txD3T3kj+N3h7OpmdvI/e+PDr/DLir/Y53smv4ZNSz/HeWecjPm/rEKXjhnMUkvC9t9tyg/0xAsfYNbbU5iYzisoxthRI6DVavDAlDeZRWLX3kPo3b0TJlw7BrPn/aKs55rRWP7nP3jvs+/Y5+nvzsbwkwfgpqsUwRtKX2oiCQKkEKwWWjW4I/DaGNL1FsTM7IDEbOXiaDfmob9Jxu6iVHbBIfcIs0kDl1M+pus92vZNbUvDoxrV+mXy+PFJgYh0b6UADlTRiYvRwqf6TLWGfh9te7NZLXSS6UNCmsgsG2kTrkF27ImA7Id293oILnur6/fRtI1Ws3k47TI0kgaa1O4Y+78/gtPp+Lb00kHXwHKPtG6WXaBmG1nNtysI0MgiyI4iq0NuodKYtp5A0nkVnSDApQ73e6CDyeGC1ldlGTIw5vwzMfe7xbjw2gfRr3cXvDT5LmTnFmDOt4vZLLdedzFen/ElXv1A8a3tkJGK2e8+hZfemYUHn3qDid3nHp2IaZMm4gH1+vv6s/chNSkeV0+YDKfHg2f+71YkxsXWuY/q44GJ1+Clt/6HKdM/hMfrQ/sMpapZYBkD+3RjI3TPv/U//LJsDUacOggP3n5NsL0WHow6YzgmXnsZXpz6KTZt3IWR5w3FuBtGITM3P9gPEucP3X4Nu9Zv2bEPfXt2xkuT70S53YGvf1CsdY39vYKvjfithSYe3z6TBX7Rx65VAQtwoP1JXYCHTvVi03tqOWCtiGR3GRwxSRA9ipUvnK5lHkss4oRSlJcpbkt20X3EtnYqeOtVXCC8Wh9EQYPXF8h4+xYB488SsWSjfMT1mmMU14eoaG21a8SR1k25qD0mxZCkLS+BIElIVkdaSQBbPH7E270oNmnQtq0Rh/YpotfXqS/aqu4PGTky9qsBbVRymMi1iqBbV8317lclT/tEKnwjwekBfhF3oIMzHu3leJwsd8B6zWHk5SvXCcFI6/NDaN8L2r9/hi+tM9nAEC0oCtul9yHa60OpVoO04i3YHdsZAgXClWYH191BzQHstQvwGEXoVQFcItlrXU9b072jWK5gmXGoLHyOtqLea3+JaIfP07zl4hstgEeefhJWrN6AD6Y/gqGD+iA3vwiffrUweBFvl56ClKR4rPprY7CNrdzOatIP6t+Dic7B/XrAWlYeFL8EzU85YuliS5bcQf164K9/tlarWb/iz39w182XMSt0qa2CzfPBrO+r9W/l6g04d8TJIfelJhaDAXGm0J/aky2N8+2k3z7j587QFOvhFr1YE30QD3XeC11hByaApRLl52ifEouKUvmYrfdYtm9sW6PquM/8nHwyvrW2welyFKu3Lmo8gFfPUge1axMNvcvfavp9tO0T45QLcHGBiGJTO3SPP4yhsf9gHgYzt4Ck9A7QF2cf8/Uey/aNbZsUr2yzs0JGbPseGP7rdmYJpXRRJC2lMg1ioiWkx8Y2ed16rabWhflx+0g0J1NNyvUugEHyw6WWyPXAiJiA9TeALCA3vxDPvfoJ+3goMxe9u3XEbdeOwdfzlzLRvXrtZnw8+4dgkxcm34n5P/+Gz75YwD5nZuXj6Zdn4ssZz+HJFz5AWmoSzjptMEZf91DwWvros+9g6bx3IAliyDevHxb9hq9/XBb83LmdEpyqFSW2jFuvvZhdV2d+Pp99//lXC3HSgJ4YfsoJ6nxeXDV6FOZ/vxI/zv+NfTfzg+8w5LQ+MJgNwX48dPs4THv9U/y68m/2OTevEB91bofrLj0P3y9YgaaiaaSbBR0/gWOrMce3P8YEOwU1OpRrtF1ys/YDOngx/QY7ZLsLm9SKYOUkwDxlKG+TAZO3SoR+mFzLDlniECXYINqUOA2tWYNk8udvoK3JqwPyFWOGRwQy0lOxab8de3Ir0CXVj6tOc+HDXxteb0oi3Xs9iI/V1XmNqG/d7thkkJ1RcDuQYdQjKtUAnV5k95xkuwduQUKXUif+NpnRtYsFvmLFDaugW3+0xUr2PjEfTADD5GVxG043oBHq22bKD1yO2ChgaFczdmUrx/g/5Vk4uaw9zvR2Q1m8C7k2G6J9fngkETFyMcoyuiItPgEFbbuiAn5IejfLnd3tJGBnoR+lHqCH+xB20z7P6AJsXxVcd9cUMpZ4ATUHsFiobIPfDKQbY1v1vSPL7kV7q4Ry/+EGr/1WT43rZmsTwO0yUtmQ2YxZ3+OtmV+jf5+ubFjO4/Gyi2hyovLoVNOHrKDYiuQEZVpSYhyKiqtP9/n8sJbZgu3p9VBWXq1lBNqTAE5KjEVhzfUUWZGcqOzgUPpSE5uTch9WH9qqC7qo0w+cb7PB4ws9uX+HdBM0h5Unt4+Ma+D0VuC0KA+22yoDCIhSTznyVP+hY7HeY9G+qW0TDbRNBkR5/PjKnwaneuIeEq1IlmSYvHpmNXGJTmRZ7a2m30fbvpeGjkMN8nqegz36Qegsv4I04SDal67BweihYANm1vp9LcPxt+6no/NKw1wg2nraoefOLPhEwBW3Daai3ux3Nhi8yDqK7XZ5vE3aH8eSmusXdTI8onIp1VYAks/P0vr4RAF6P1kogc07dlVr9/fG7Rg/7mL4aOgTMhOxXr8/aH3u0bUDi4O4+PzhwTZk7ZQkCampiejQPo1ddzds3c1Grqjtjr2HmHHBJ/tD3kcbt+5WXTeUdXv9SjuP38eW0blDOn5etqba8tZu2s4EsAYeCH66rqVj3qyl0Eo+aCUP7G4Dtm7di0FDerN25LbRoW0bvDj5Ljz/xB3B5WgkCWXl9ib9nsxiL4rV9lko0PFDx1Zjj+8u8KHCpVy7vYKPlZ7tkFKGl66XWWlcv8YNgdwe/CLsbj2SfGX4W9BBqnGst9S1jPaQ1LE3UmwFKCwpqrc9VbrzGaOr+TsfsBeh0FvR4LoFmbxXZYg+EUKFBrZYA8qycvDSfGDGBBGXn+LGu0vcyC+t38ih0xtZP0WND9ml1qBh/0jb7Y9T0tLBWsiuLV3SyM3KgPRyN/JdwNqotuhkLcDfbcyISvSzeWjR5owEWIRSVrbcVKJsq1unuBQcLpKRbyuvd707swUM6Sog1mxDlvoTZ8tWZIgxyPDHYmBBOlZ7NuL6CiMyo/VIdu5FqWEIMg1x8CakwYJS0MCVBBkxGh+itX5ke4A41WXAkahsU2Dd8RZlTMbvUwxKAReI3Y585LvKW/W9Y578G2L1RuTYGnZz2Cnmt24BTE9GdKF+4a3P2ectO/ehR+f2uO6y86tZEcIVuhn5GvGD0w/sbsT86TGKddmr96JYtuOCaB/IPTZaH/CfUn4OSYcGl9vY9R7L9o1tq9Ep20QCeF3H4ej4p5JyZpeQDwMsMKmR08Yo4YjLbc5+H217fZTqK6hPREWJE//mCjihFzBUswoH5ZPgjYqlJ79W1++jaRvw49YU6TF8j9Lu5A47MSQ5F2+rAtik8cILH8WpNGnddOOqKXee0y2uNrxNbRubUr0xbWtOF1Trr+wVEVXuCqbF0gt66CnYU21Q13ID3zkcLibkAp+jjAbM+mYRPpr7Y602WTkF6NQ+XWlPKkEQqrWtax/VR4VDufYE2te3jNrvBehkF6QiZdia8qjGGStQ4FJvKaq7H81rMikPvQ89+xYbgVNaK9ZbEqRNSn+vqqOq2x1SsyoPMI05vhM0gNOpiI4KjQsDO3nx4nUyTHoBy7f60TtDgDHWDXuxAS6HHsmCFb6o2HrvJ81+LetzCjwXTUTJllXwLPy4/vZUBU4U4fd7mDWboHtVKPusHE5EwwipVIuLLhCxpNsFWPDzCmw9bEfvtgLO6uPHZ7/56k0PqnoysYNDY5BRUV5dLNe7brXqnlxawKbHp2iC7g+/2USsK7fjYY1yXial6ZXrT2wa2kYp/sIdy5zIq1CqqmksyvlwqEhucJt3ZIsY0lVCpxQK/Kzs5/fSZkz0n4qu/iRsLU9GcrmdCeCuZRuw2zAE3q4nALHJiINyHsQxdxHAIinLj9VUUCJxyJY4eE3R8FitbN3p8RpsLu6J7YmdkVYqwO1QrKXjbz2DHPGr7w+Bik8K8NM50pSTSziK9kfZ9pe3d6DVCuD8ghLs2nu42ne79x/GqLNPUaYXKonpkhJig+/Z5/hYbN2lOHwXFJYgIb66GVySRMRGW4Jt6JWWURVaRqC98mpFYs152HqtIfeluWljVgJLHDo3C4S7OF5NIK8mwxbLlZtJJKVCC6RAM3l8yDUkoadcEQwcSIMWlEucAkvM7SIrFZrRTAJYhsshQ/vJZKwX3eibkYaunyfhPszHm33jKN43omBBLF4Bw/Z2hOiT0SkuH+e03Q03WUEhQyDrkF1ClFmCrfTYWXEDPrnsNiAon5sigJvaFqr/r2DTsnQ/bglw+r2QWCU4EsAC+vbsWq3JCX27Y/+hbPj9dR8Fm3fsRbdObXHgcO28mcSe/ZksToIy8GzboVzPOrdPZxl2jiW792diYN9u1b4b1Lc721dmqxuCR8TBA9k4oX87/LVMRplfBg1+9u5Vmcy/sNiKnPwitE9PxXcLV9Z64AgHEjV+OO16JcOz0YWXrrczy++yLX6Mf9+H926VWAEFEsD0oJcYVQxYqsc6tChtlQAsR1rXhv3Do+OhgweOci0EKugiyKzKWyBrT0NYBSeiZSOiC0R4M8pwSbd/8G/ns7C8dBt6t92Hvu3qX3NUjWqgdI2oKYCPmAOYMkBUKYHctsyN/5UJWO/34aV4L8xuH8p15B+sQ26b3miLvWy+bsVOrK9QgnMtcYEcwHQVqL+/gUwQ3dVMEAEKxHKskvbiDF9XnOPuCeStB9KAdEFtMECJCEyp2AGY6cHKi40L2sFNAdK97YiiVJKFWUByW7iS2gHZh1gu5cRoASv3d4ZX1EMoVFxDhRgBppjICypuThqlOmjoi4bEqkKWiKwcxXRNbgsUxHbaSf2xdef+YEYHuoD+7+uF7PO6f3ewizQFQWzerhyAND9ZlzdsUZ6K1v+7A4/cdR1Ly0MZJ4jhQwewiz65PwTmGXZSf8ys4jdHQXD0fah9aW6StIoFuFx0MafwC+KUW+1PnYcC/wCCQ8tKA0eSAA6kAzN7/PAUSND6lYhhqv6S63eijyqAYyKsGpzRpIg+j80NweuB0+eH/es4aPINiIML0ZoUtFyRyuNXBc60PAliRRRMWhdO6LsPd+4n6yTQQ+dCuVsRBxTlfSwFcEsiQqZRb5btQXKIlTlhBRpRom1URgJSk5Lw1EO34POvF7Fr381XX4inX/m43uW+88k8/PS/l1nmiDnfLWYZbLp1aseucY+/8AH2HszCst/X48Un7sTkF96H0+3B0w/fyizJx5KP5vyI+Z++iInXX4JfVqzBiKEnsEA4guojEF9+8xMmP3Y7/t22C871O3HFOWeja5d2OJxX6cb2yntzmLscxWEs/2M9y8RzQp9uMJtN+GCW4l/cmkkSPfDaFWHVu5uLiZIVW2UmfqmA1cYDMgbHuUA2RTrG40xWwNIdrYakDPbiiU2GVqsDfPX4W6a0R5JUCnuRIqz85Kca4hMhKwYiA2dudSI72YY/0y3oJ62Fw6zFYacWfTvQ+VB3oHNUm8TqSR1idcjPre0G2GAVuNJClkGpagDcKpuICoOEDS4dywaxOcmEtO4JyI/vhQz8xObrVuTEUruZ9CjikxUXyMP1ZICoLxNEVUgA9/KnIkW2IH9te2BgEUwm9bzUK6MhJ4pb2Ku5UIt133QjHxIInbdBipKAzH2KAE5WMlqlxwNOnw4uvxr4VnIAJiThgLccP330e631ayURKZZo5NnK4KlinQ4V7VG0P9q2rVoAz5g1Hz98+hLuvuVy/Lj4dxa0du2l5+LhZ98OzkOC9N5br2TWDRKh/3fntUyIUnAbQSKWLtwvP3k3Hpn6Dst5+dyjE1hQGs1HfPfzSjww4Wq8MuUevPPpPPTo3I5lfZjy8szK9cz5AfNmPo8J143B0lXrcPF5w5g15OFnQu9LcxIdK8GgDqGVet0YbpERpwHyJDN+ShuEUeI6eP0SCyIIpA2LBAxG5QIR5fHBuF/x8d2dFgUUUn7JQPJ4LaIjqBgGE4M65eT3qMnQk/xmdDikBBgRKZImogRwoAqcbrcS/OA40YCB5nPhzvsCZ8fIOFHvZAKY0iSZI6jyn46ErigwNx460h0GLdxuxddNEcDKuPtPS1fAaNBhwaxX4PP7MXPOj5g1b1G9y92++wDGjp+ER++6jqVCo3174HAuflhcGbx7/5TX2TXyyxlTWazDi+/Mwv/dWV1IHC3/bN7JrqmUwYFyqlNQ8Rsffon7JlwdTPe0+tdl+LptEu645xbcp9Ni6S9/48cffkOvgR2V1H9+HxPxDqcLt99wCZ64/yYm6HftOcjuKeFAguSEX02BFhPvwsb9EibM8DDxS2zYL2N4cuX1zJJSBlhaSzEMISiA6eIkk7A6tLPuWdt0YmWQHSWK2PdqnZTYOiQC1eDmZRtw/t/FuK2DHV/1TIDVAMzJj8P1ycXQaxDcZ1VJSqUsDpUpvdKTzdi9o6KRFuBCxCZooNWJ0Hn98Fs92OXUIt0ALC704uRSJxPAbXqmIttggU5wsZHJkoMWmH3R8MCHtj1LQrQAKwd/+ySBPQw5quwjnyDjF80OXO85EY68REAugt8sQVtRAI8pCSL8SLNYkefTwPuPGnQvC5DyDPAluYGcfUD/0xULsJoD2OZWg8r8DlABOSLbY0V+cW2/Wsq0oPNLKLDamuRmozuK9kfbtrlplOrYtHU3bnlgGibdcz3uv+0qHM7Kw5PTPwwOaxEkWKmoBaX5oVySazdsw7g7psDlrnyau+uxlzF10kR89cFzLPvDwqV/4okXZwSnk5Xg6tufZCl/Fs15DcXWMrz2wRfBFGjEuk07cOdjL+ORO6/Fo3dfz0TuzfdPxc69hxrVl+YiNV0XDHIjC/DoOEUg/ZB8InIMcbDonShxRCmBQhEkgGPoiVb1AW6zg4aBBOweMghYthK2CvWGYdPAEEEVwoK/nww8n/sr3jH4cYKjN6QqabeT/DLquQWFdRU48v8jlnbqA/d6ReBlucnP3YEcWyw7ByKpGpxOJB9BCaKTwlkAm14MCgaf6uRCQpFGsia/NAOPPPderWWcPGp8nVkb6HpL18H6INF7wz3PVPNdnrdgech9TxtwUbW0YMTqdVvY91X5Yv6v7L8qnyxYA5IdsijDKMiY++kXePSdLyjZE9JlC95+fxIOZ+UqqW9Uh28ybNB/2LlAaHWIhQ1WVQCb4134Y5cGbm/lfWTTQRlR3SuvZyaUtB4BHJukFGJQkSkPbb0CuCOSpSK41AIuDvKdDVEAB4oc5DqMOH+7hIy9bly7PQdtLkhBTowOmW4temU4seFAbZNyp+TqUiQlXtf4HMBlhUH3BwqAW1mixU3Ok6Ev0GCx+09cbVV+n7TochRA0Qldip1Ysk+x1K+XDmNMB/pNhSNagIvLgcIymbkmdE0V8O+h6tt0QChmglrr1SEmW0Jpug+J+euQ0+F8jDb9DZtLEdcFmytdljS5BtjbVkDI3cvOZXdSW+Z4QgK4zKMIYC8cwSIYRX4r87DiNJ1Gm91+XbWW/TfE9Pdms//6oEjlOye93OAyyAJyyc2PNjjPT0v+YP9H05fmIjVdD+lfbTCFzoWJJBj8mJ84GAW5OUwgkAAmC5kxkgSwRdlmV0kU4pwCywm4v1s7wH4BypYpaezIBYIc52kI3WH3R5Dbhw83u3fhxOR0/FAcDx98cKQ5YM42I97V/A9hx70KnFeAUKH83nvjEoBDijtSphuwRFUWCjDH0wW87vRQ4QbFn/i9yqONW6+B11fpgkBR8f5AVRs/Cb6QtUSrRxPwXRZlGPR6jBh9PipWbYDf58f155+FIUP7YuKDz0CURPjD/VA3WhDjL4PNpuSaNcW6UHS4unWQio0Fq8FRdUuyhhqjmHiGpwm/OqUdM5qB4rp9wBtFwPqrUrPIQhCNjs2bIu2Fx6pjzjtlCD01VaAYBvkBE5luAS8cAB4rlIAYoNQnoV97oU4B3CHBDeUwUSyvcWr6zCMiaSqr7pUWIrmPWs2tzI1/DvZFmj+GnXsWa1cYSrYo6TglB3rLioZJ2m5Atj2eidW/dPuQoqQ+ZlkgjgS5QZAA7p4G/Ftpd2P4BD+yxFJ08McjbrcRpenlSLNvRz5G4u7o+fg+T7lHOIpigxpWk2eAUxSQ4czGYa8Hfr0JUlwK0uNzUeZRhLJTcgQzQBQIkXENbUkiZ9y5lZOapoP4u/J0mmxxI03yokwyYNmhIrgP74JJr1wkmQU4PXIEsDlKjSTOUkpVHjI44aLUaIPORvlfi6hmJAu2EOwaNjQeCQLYpGZDsLh9sHp0WLq3J/t8Vsdd+CMuGp5sM2Ip9Z0hipLmIlIC4MgNgNCIPmRbCwCvckzbfAL0WkelAO5siCgLsKymJvJqJPJ5qZyoukcwZAEaFizXpJwHjYYKT7z0xJ11TsvMKcAZl9Y9LSQoBZlq1RVEmWViGDR0MK658QoY9DocOpCNh+9/DX+t2wKhBfz6jjkmC6JQAbEsoVIAb6u9XYftldXQJLVCHrMCF6uVwBrD1f8HJKYD79wPVCildptMspomjJYTFQM5pX3d86W0Yy4rSd5c+KmcNQUweo9cBa6mAI6Rq5/f1mIXpM4mlHol9O8gAitrX+Ojo1xsZD9R60OhRwNLqLGc0fEsrzo8LsBuQ2ob5T4jbEyE0Z6m5JuHiMHe9liQnYn2ZW7siTPALNjYqZi7oV3Q+hud4IIoauFwyyiy0ZB8w6vemSPjlO6Bksi1z+vDYgkTwDhAwe/l6Cxlo6thJSw0OoB4xOYLkLyVdQd0ecp+6xInIDN3P+SMbvCndUHbhDyUqS4Qbp8T+pKoYBlkztHBBXAzQA+pVIYxIBAGdkkA5H342dIT7qVfssADyaSrLIfcJQJuGjWyQFizlKf0Pa79QOYugE7uUy8Cfs4EfBQcpWFD4wWhBj60YsiSHbAAf7+vFyo8Boi6cvRJ24cdQnfQ7TCm1K7cHCNFAJtJACvHsNHghnBwa7XpLjViio7vQMnTSICqHHoCAlgSITiU5PYBSABPuGUqfDEeqNnSmoXFK/4OphyrSdUCQ01ClFiuY/ZWI8PlduOKCU/Ap/pMthUN8Hl1EMwCswCHgZNDwxjN0MnFwTLIUXEuFJfX/jG3Wx0gqUnz+UQvRNkPP6XoaqwAJkGX1FYJJkhIO3oBTMuifm1bDf+J50GmZdZlmW7Tib2kuQ+hWBX7We76q1XW5wNshh4i5QVWncSz8+1oC0UAD+1E+7Dm8SdA1HhZDuUUrYcJYK2h8RkgaLAlKUULKceAHRuUbVmm3Y2OmgR0diRi/6F+GFryLxPARMIOA/KsivX3d2kfBiQox++R3B8C7ApkgqgjEI44KJVgmBdw5EQDch6S4mVcr5uDQo9iwY3Za2BezxVwIwo6iHlGZq1OjxchZO1hAlhOJwH8B7JUFwhfiYflXHZqRZadg3N0RI7SasWQX5LGoWVpoGhY9HydUh7z+30FgNvJhm58qtUw0nyANXqWWwr2/Khg+jOsnKdMHHgGPFQNjh4SbJETHGVUyyDrsgzIylGypnwsb0PnDQJMOuUmEUVlf8h6ESGQAA74/2pMfgj51dMlVqjWIRYEF+rwZhggSQIEVQCTtakmXnVTaR5RTZfWHFTYHSyFWl3/lEf4qBDEoAAWNH7YNUJQ/BJyYD/QyE4zbvNxw2iB5PWylG+EKcaFIlvt7VqfoxzjNF+5rEWCxxbMUdso1Fy8jKa0r0my4gIh7t8CyV6mLFvNMFCNNh3ZSyKKgkUwCtRA5VCgcshUAIaqPkYrCeMY+wuV44EEcLckLwsaq4oQEweXKpZT1fuBTxfiSEmMKoDLChGXqIHGp0HMl+3g90vYIebhL81B/B19iPXN4I2Ga61S6pueUo0rUoLWXyqBnJEQuvtD1UA4xQJcmyzRyuIAfE4DxBIttIlapMfKyCxX7nOaQ8o9cYuYDWh8oBJ6UpEeyTESxCyluiMJ4DbxIso9yrxykbIvC6N1odc759RL5CitVgwFwAXEgTNKi56uHLggYtEe9RGy3Aq3Wjgh0gQwdICWhoB8IrMQUPozHNoOHNjKTOP2aENl5HSEWAaNMUZ2gS1bSb52ArZKOdgvFsHqEyAIikVFR8G7rSVI5hhA+SsDQZ70MCeUVTejFKGKBVjnY9aaptDarvlM4Kkqt64MwhQRrr4JapqwRxQh+eWgBVjNzhQW29yk48cUBa9TzfVs9DKxUmqvvaStOT5oohQBZ/MakUzZQJpyjlcVvQH/1qai0QJxlG0dEAoyoStQH0zr8gNWLcBmyREUwCy1WYjIAuUCVh7wU/2KvzSxt0gZA3DJItUOZEUxqtKlawLKqWQkdbdMEXhOqZEBcOT/m6KDeX4GxBI9fJId32s2sx/cJXnxq04J+tuxvROkQi20+6PgzI1mRTHI+gs12KwyA8SRCaRCo3amGucA4RX8KKTSkDQSuj8KPlGE1Stha5bq/5ulWHUPiCXwWGzsPWWCsERrIGQrKWL1SYkwmSysmLzo90Igf2oSwKrBjHN08L3YzBkgDCblBF9WJjHfSIbfhwpV9LIACp3IsgeFO1Tdh44w7T7FoWufWFR5B9qiBC+WxkQFI6ejIsQCbIo2QCrQw5EfTaY/LNVWDkV7fcoFUXKK0JmOgXWnNblABB7yLDrApqQ0DJAvq9YxypfrlIJ+0o2FKgxRlbTWgQxZFJgPe30W4IAYZFbigD9wuCNKEHzKdmk0fugNQFVX32D2CyaAW88203HDKlQ1kliDIVgGWRvjZv6hflJ7NXB7AcGsWEwrXAYke0gAN+Ecr9rmaC3A5EdMTyFk+a0ohb4ws5oAHj1IwImdBSU/bUIb9p1EBWu8yg9qa+QwO1ldiUH+ysA7SrpkdFdagfu3r77vBvXQsewhRIla5IGCR6NYLvUjEJMUFMCDXG2h3xYDqs+90rQBDqHSnW6zlIM9QiH8soT0b1IRv0Rpt061/hIZjXSBKKkA8kvrzwdM5OkVYRt1WPH1nbtBhF+ngeAQ4S5V7n2HxGKUMIsIoMkxQG+WINjLoCktQLrGCpsaAKfxVTALMVEYqosIp0G4AG6mDBABcdBGq+QZ/FEdyghgJVcBVQiS05zBEP4/TSCbhbZQGfPKFavkLCxTBFJBrHKBDxRIiASMFi3EQB5NnR02sfImYrN74DcoFpEYSc3tGAGQXy+5NxA2sw6Cr7qfX6ZbRhTlFA381k3M+/zdz6tw502XtAoRTEerT1aOcSqGIQfy/qokmAGdOqTLrMStSAweFaJIz3UMSZIhQECsci9n0DA4g414oFVAxwsdN3T8NJYkgwZ2NYe7LsaFgtqpV4O41WPcVaFDsru05S3Aqv8v8jOZxNQVVlqAx54k4L1bNfj+YQ2WPCbiWvMKWEoPwVWumjMNHmbFbAzkTkB08SchVs0GQegcVQRwjYpw/dOV62OU34fteV4YRWXejikhRMJFq4GJRcXouk0R9R377sVvtO+rIgA/abcwi689Jxa+bAtkodL6S7RVjcmhWoCrF8Soe3qeKmzFg8oJsu6wBrBooDlMnwUUCRUoF9w45FOEsibPCFlNHWrIO4B0TWEwAA7+imAGiEJtpOSTaVl4ENxxhvxaSdgFBHAHqZC9LrYqadACFEgyYgQ//LIIsVzLgsfsFf6ICIDTFClisESsElChWgizk1IwCHlqNbjIOBwpCE46pKvMo1nlelpg9UGOcUN0GpEg6FjlqEipAhc4xosNtR9kstwCBuudLCCQ+QFbJFTWCQudg1l5+HL+Moy/5gJIlNS/yjS6req1Grg83iaVQm5sW7MoIyXeBDnPBI9eRJ7BDU95KWtPXjCU8snlFlG4WxExno7lOHyotkWtuft9tO2FmER0LFbmTu5WAq1Whs0pY+MBZXqcBMS5FTVR2l5GUWZxi/ab5iXLLx03dPw0NuF+klaAo0QRHsZYN/IbEMAlshMkeb3lOiR7SoGOZwIjrgD+Wgg4QkxbZT6GFuBABgjV9UFfoFqAE9Mxbnjl9bZXihsv4nM8GaPB72uVEs6y0U2OvY2iWLBjr1CIznIiTvBlYJlmtzLB5gViNCj1iujXidZb+bDYKcaG7HItCxreVuRDD8kHh19EuxQTtuxXhOGRfIBTC20Q/DHwxbkgR1Ee3dpPXiWCA8ukXRjpU7Ly7NRWWn+rukCEagFmy8iWcVqPQEnk2kfiSaeUQFggw0clsku1aN/FyB6EjQeUh4ODgmIQ224vw2B6oMw1wGmiojoy9HkH0FaTHMwB7AalQFOOh0Ix9PR0nPqJDMXRyt0fCG++sqtj9A6UigZke6pbiwpcPmTonCh1mSLGD5htgx8Q1KTqdAEKXiNsyolfkhBf6QIRIRZgk0GGZFV+9zLJXS3oOdsho43FDeQZWTEMJVNuZFSBCwjgvDryB1Eu4Gi9E7nlUIphHIW7C4mYNz5SAymrQMImPTYWWVZrk6oQNbbtqFgZ/U7oB+PPGdjTPQnLNOtRsH8Ha3/v+SKG9JKAKOC9T0ZC6/Sj5M5d+PCL/ago97dov4+2ffrwMbhtiQuyxo+Rd/4KfV8B2igBU9/2YFcO0NsoY5zjbHhcOvx7mxvzPlvaKvrdVBK1Mtx2fTAFWkMW4MMVDiaAKSNKUukeION8YOiFLO0j1i2BvK6ymFNoFuC4Y5MDWA1KleylQHkpOsU6cHI64PPLOPtZL4ZfeTpu6LwXnbR5sJeoZZANlFqs8askt4LOXkUAr5CUYC6nTbnwUy7gQUl+mA1AuRPMdzaKpUjUQlvuR54VGCz5UeABUuN0R86WoQYSt1WLkvgTnViXTcdD3ffP1dJB9EEy4v1m/IRK669Og0blAA5Ax3t9LhBd2wB3ja7Az1vKUHggBtqDUfD3U/ppOGBi5q9DonIfPOS1sYo5FAxe4tWhjRbw5O1HW42IMocigK0uD3QuiWJLUSwf4cGAExLhr7LCIP8vIRcrApgqvu3V0kWt+glT4HCzaQSlBIsEF4iYKFFJHaRmvwjkiWRQ3kZHBWwW5UmYRL+oEYJW43DGqPVAtCpisKiK+wOR7Ragi1KGr+LrqgkarlXgXCJEp3KMZ0u1BQkrhhE8vrXMZzjcyYgRIJepQ5KxsdCUVxa3PqlL5fntj1f9+606JESH//GdTMKDiPagKBdYvkX5eOkQ5ft88vk0Kse9ucKrlEMOY5IlP7x25ToeFedEYQMC+GB55TU8vfwf4OtXgZz9SiW2Uy6CZ+J0lPU+reEVVnWbOFoXiKAFWLH80lEp5B3EFWYlBmPFVpmJuJnuMRie/RyumpOKstxAGeSmpdkiP2AbnLDAgO5+xZpsLVNEpdWpYZ5AfdRAuP7dTKgg/yGyCZd5kWuVESUpD4jxR8oWQw8KdGz5vEjxqpl3YhxYVVZ/O0rNNkP6Gy9ol1Wz/qbRokQhmAM4VAKZIBQLcCVReuCNGyn/OeBNVEQuCwYnPAL8Ocr7g4IyOuIWfNDGKk8blA6tc5wAbUku0pBfaQFW/Y1L4szwuXgRjGNB+F+Nw8QCrK1QXmMMDuwXKyNkA+SX21k1OIIsZJFgAU6i1FjFynbbtB7IgejwALZilEUrwQGiQ8MuDOGeCYJyPuskHyTVB7hAdNcSggaTcpOMsznoAyKhClzA/1cveZDtqS3si71k7alSDCNWmT+cSY3XQFIfdEosBogeNdWbCAymwCIVY6JyDNAxkR4T3sc3kaBWgRNj3MgpFvHtX3JQAJO4KWK/tbIvzKVupaJZGJMkeuBXKxxGx7mQr4q5ugg85NODf3y6BOzZCHw6Bfj6NSD3AKAzovikCxt226hqAaYsDk3dfyaLklJN9gOB4DdaZP4+XB6lCOC5f/gpapdlU6D4wFVrCuBWYzacYugZIGqKzA2Ssr4TfUq6tTzVJdfmVu5rgUC4gT0twQwQjnIfcqyUhUI5vsxR/pD8f1FWhDZQrqNGiwP/HsFqTfGLNWMYm+L+UNUHOD1eYFZt4oSOAn55XIOeGQJKygV8sUcRwPr9Sh812ZTvV8njSy4jAXzRqh9wrhHt4kQIsow0fx7cfh0FGACK9yQKE6IBB7cAHwvCX2W1YujhlNUm9wowepSLConc/TQuWoOC0vKghYzEhMEY/jfK+BgdRNX/1ybV4bNkK4aTqsKpQQ9iBOQCDpRBDgTB2cgFogpZbsBsUH5nC9VPtagX8XCvAqe6P5gNLrgq6ro4C3BXKYZhjqkjb1CYEROjCf7OVl2l1btHOu2HyjtsapJyA6RRAcrxGe4kUlg/Wdti3ThQKGL5VoqIl9EmTsCp3QUW0a9X810bylSBFcYkUAo/tQhGTJyzQReIsirp/vSJVX7rPRuAz54G/H7IWhr3b2Cf1PT7baQbREqaDpdel4TUnmpkVkl+taIXZxo3I1VTikKPCb9uloE0Jf0ZCrOVvPQO5dwMlHZuCuulTDbqR77AcX4jMkuU86FUVvYJ+ccHxKLNq3xXWuZFcTlgUgPv9EZ/aDmASwthdqmGFENFMKNEwLXBoD2yS0NjcwAHoHpGZLUmeqQLuG+UiO8ektAxWUBWsYxHPjdiq6uE8sVAKDZAsGmgVfP/HiT3hypC3KqvTIWWEqvsk/hgJgsnJPVeWphIAphbgI8FXAAfR5JSdJA0Atz5lBpcgCD6YdK6sc9fO4K9wGplPpIBIfj/7H0HmGNXff15Tb1LI02vuzPbu7fYXncbY4MbYHoJLRjIPyFAIJCEkpAQAiSUVAgdU0yzccW41+29Tu9FGvWuV/7fvfdJo5mdut61Z5w537ffzmgkvf7eub97fue8GirADptUqoTGpyXA5AbAQTPIJR3wUneCsFhIGhgPPse2IylMnkYk1TGbXgm10TAM96vKAk20KBCTjPBNRRpsu1kT3NI/v81OoaT1jpYNdLa3sG072ssejA2VrHRDrgXPq2C7PVm2rWZHDn1pkdp/3befkZU37tQbX/XBjkSmoy1LuAIsGeFSE7QxmcDlyWJslmC24rQ6nxZR0GPgSyDx0Xrzr1a075oKYkdG5BIExQQ5+8JkEKs3WFBdZ8S1l8kgESVF+UMRb14xSP//ZWIb7nxPANfu1mAkYl8i1SDrps9Wjivn32hF/IA7SOgRqfLKtUjofC3L88iqHDY2svvjlspUqQI8FmPnkKZzPs04PwIshEOQMmyfyQJbkFEEPvIaHgf+mcMP/yxJpQizYaEewNNVgb/3IQGfvEWgkee/3avitf+o4eSAiCwnY5REL5PTqc8CqZeR9T69Aa6IAU23QhsxweUUIAkaBJ5tV5YjDXC63GqZAF8wLP278RKQP8S62MVlM2apLVBv4dzew3Q2BwMxWX8VhWFYrEQCoVcTphBBCj0sIVfmgbzkK8BuK9V6EohiDrJe3Z4AB7EUhqEBNu+rKgVOs3IQ9QbHqQgXyQE5zubz6f1fXNBMBkp0CGJa6hz970OHVXSPabD7dOIfNcD+KtA+W4mul2q/sxjR/WJ/9SI7njdt5qj+Efo5LpCKl30JE2CLHdZsino9EwmX1ZWftQKcQQGqroFP5sxsX5SBizFSqLlmIMDFam8mBURGz6sCTO67BB5bHqtxsNQAR+C2qrhmVZ7OqMvjffAEJKypGsf71a+gVT3EnAz0avdQ7jw64Mqwn2fL3SDXQCtwMOSUkhVaU4WGNTVAwJwtEeDBKPt7Os3OpaxE7pbanATYMxqk8cCqUUEin8WNmzg88TkRn7ldoDMxNV4Nl7XNvq4L9QAux1ldB+y1c4hnNHz0ezI++j0FROFWRA/PBj5St62UANerv1YEcYIgEIImmMwi/E4NCd0CrSBnIepewkES5TzFZnIZ54elz7KWAAHODLDd7DGyG0pvbnqRfkG3TXy1EGCDiZvQAIvTTKfpRCllY+8p2mMtZZg99lLVm6PdzedCUdL0YcrLHCzmV0MFmC8lR+WsIvj89Ns9qk5ExYp5gVqnLV1oyCnsQVYwcchnz22A29uhYX+nBptOgIkEwrTkCTAHg65wcZkzJQJ8sFtD16gGi5GjJDinV/vpvazcJHgpxiCn9ZKkVQYvaLMSYDKlnTWyCnkyYsIlUwLXuKgu5JypAlyUP5BZlOJAcoGNcOUhMzvwGMRwH/2ZSBFu3FSAJHA4PmpG2piBqGjwpwrghTxes3kEH35zRamZtSv90qy2SOx9DFlYYUBDxg0+yUjbSJo96N59lQCSp1JsghsMCbi5sAbBHrb8pMCj0sDPmQLn1bsSFW8Om3cC//shEQ0VHJUm7Otk5PS69bM31DXrCcnnUwF+5jT7zN4OFdf/g4zf7j33O3r0ZjfTURedHZTLqsJFnI5kwZtlNthSbKhyq4jpDXDqEZV+btxjw4BnDneMZcwbS/kJtHQs0IJiSf8bFSyIZqfvrtVncdhD41XgAiEYyPSULoEgfrhTwCXYcDvssL16NMBOc6kCLIvTV1CSKRmalT0MnPwSro5NI4FIEgnIDO8blIkEaKIKvJRt73wikMiyB3nMZSpNbRMz/UoXh7xMfHE17O8iFWBd2pQRwZOLYinDZIYQZ/cmn5TGiK7fJPjVixMyiGKCGL2X2V/50JLzBpFvZCaa/hIZDZk5MgjS+jmejhixq5mbvgJc1K/ORIAJ+S1KieznVwFWNAE2Lo6NVUPYoFTjw9ndWNnVgrzK4dk0qyZGQ5UYH78Cl/ZlwKsaDHbmBaZJCsZyE0lq59sMd1APxmhL+5FPsApvWJeT3LGdR4pWfzm67NZoE7arDYg+yZwrCjyPpopZ7o/6IMIXZfdZxZtHWy05Phr+7QEFuz8n45sPMjJ67XqqtpsWVS5gcyM7pw90LZwAEx31xk8WcPtXFQzMUEEu2p1xujRumI/Q/VOOPAnAqmTShmzShlq3QlPgNE2DsIddQy/uaIOWnZhtWsZLw9JnWYu4KuZwilBVrTQ97DBl0G6phECmt6ZBXCQXhEZHgFZtiT8oCfIiuLxAGwCmamHffSWPsx87i/fbH8Wor6KkAbYvcQJscRggRNjxTs9gVh6OK1Cc7OHiwhImB+VNcHoFeJzEX+sgjgBXr+XwPx8U8MwXRPA+fpIV2lKu9tcZyVQtI8BhlwOcLue5pAUl/W+2AOzvVCGZFEg2nUzkJ9KxliJ4s610rO1qGvmydvpf7WFE8dJWDjm7fpxzAuykE2mpwmyFkmWPScFRmL36q6N4r8tGjbhyLQ/S51tCLDS7BrhogUYIcCJ6XhIIm14B3jbIzrndmzjcya+gP/cdqMYjT9QhJopIqU78yP9h/Fvd6/E+/kMQfj8C94N6KTSQnpkxLgAH9Wa4yrwDaT0cqFhYJh7ARfmDOaegUWUVXXXMCaPeCNfon8klhyt5APuzaqkCnE7IuOoLMv7l9yrSOWBPO5DKAn4nd04EcxGv38rW4cV2FUPTq7fmRGgOU4YUl0damHhTO2ZYkIe9Jztuw7YKBcmCFUq7DD4sIWsScXhT07L+9wJimQBfJNQ2MGITHCnAprCfSZNbhzkAITv9CRxUOJiNeiykvPi75M2Gie7Z6aAm2A0vb1YnjXY/+Xoe//hWARYDcJfjIYxW+MpI0RJ+WNLnJbHG0pPvZuiiHo6r0BysjFShW0ot5RQ4i4VogPW4a1GlU3cfu5nDni+J+Mmfibh5C4/mAIcNm/iS1R8ZFC7lan8DiTvTt3nc5QSnV4CL9md79alX4rEaL0glGYSSWtoDHq/DUdLDIjV5hmMwzAg/8VN1NGiAkc1yeNSle5ztZjPSOd3K0klS4OauEMb16z4fM2D9Ch5Pf0HEbZdwC6sAJ8srwPOXQIgSB0GXDbypewDViTyETheU/IQMZfjXzdSN4HHuFijQB+ujA3juaC3Q7YTGq9gvHcOFANkXXTwj/UoX2448KXXqSCjs3BAjQEBj0/1iygprnu2vKvcMzwPioiEaqKtGtaI34FZkcaRHm1SFJXlTL55l33HDhukJ8C36sblv/8XtSzhdRnqpA8Q0SJp1OceoBU0+EzTwkPew82n/lhXIk26+ZQu0C4ZlAnyRUNPACOxAbw5OrUiAM5QA8zM0FwTzCuy6RZY5t/gJ8L+/T8BzXxSxVvdaL4dk4EoJcDHd5YH4o37lHQL+4mZ208sWNGrHs6JitCSBIK4ZS1n/bCZJlzoBHtOmP84kFliysYGOd4mHYdAUuIxAdb0E61f1455PJPH/buJQ7SE+mBqeOcVIfkMt96qpAFd7JxwgIi5bSa+5Ta8AE/0vgaoBB0MuOHQCjLgBxiXMgausOpGyyhgJnzt4I7IPAkeAh6gHvrhe2kz6Kwq/WUI6y+5jBlduVgeIImK61l0NGxCNatQj9t/fJ+L3fyVgq1N3diDVy2KgyLQSiDBQDFZZgAa4qP+VFBX/UXkjjg02wvwsqzavvL4XfE2KSnGEu6vQk6qe2M7OHlwvs06xB/lTuH9oHhs6T3QKjAAbx9h2JMq2O5pn5FXtMaNcPGUeMZUay2bT/5LrziXrHsD+NE7rDWnlePY0W8b1G87d340VTP5AEvHuP3hxixGdug5YgYpBbqJnoBwjSqxkhVawOKCOKFB7SQEJ2LOjlb1puQJ8wbB0mcYiR61OgAcpATaXQjDaBTc1uJ4OwXQeTt0/U0waIEkvfQrqYsFnB65fz1HLl+vXn3sa2awchHG2D4JCAQZRw39+gMPbL2c3m0/+RMYPn2Q3nBuqDpXSk0jT71KuDJoNaqkJblCbvgJMvIBNFkaAXUs8DIOkwBX1v1Yphx3NrMK1r0PDXd+RseXTMj59N6v4rKzhYDVlXhUE2OMSSsc5YhXBFXJwWlSs1CNRSfNbEfuGbHBW6JXviAEVS/j8brSIJT1sj+7tWo5jfWy7A1UkHpmd4/bzCxRbFKgwCMjqvrhm1/wqwGHdPozMgP3oP/L453sVpLIatjTz+M1H0vhrxy+ZSbw+hT8JRbkDlUDoVUKra95yhKL+1yariDZZ0CynIA1aaGz12W1xjN82CE1Q4RpyYcuzh+l7xYKMN57hIUHAGX4Me3nWNHeh0C0w4udLOWjYUcQoYCDLtj2sJ+xpvZO1vuIge2Y6TDPEXOsSElNwBJKse+xXptGuW5KVg1SAZUXDmlqOavTLccs29ux69vTCEuDOB8QWbpiLYz/fh4Iu8ZiKs+kkNF6jg5SRtBuFvezi6WsSEHfqg89lAnzBsEyALwKIjtXpZvrfYL8Msz7NRCUQ04RgFDGWzMBpKItDXsSV0Bs38XSqk2DHynNvzjX2iRS4sJDCv/5JGtdv4GjV9wP/reDuZzX8/Hl2E7g+cIT+zynEQ1dY0sTIni/o1VAN3TP4aE4Kw4hlJ0efLuEUOLsxg2oHu2F/9uca7jugUY/YniAQTWkwShxU/e8sDGPppsFZSQiGngIXFVmlc32DUopHjZTJ/A/0S7DrBJjMDtQt4TCMAK9XGB15OpMxFcf7GQGpryYzOToBTi9dmY9PAgo6SbO4sgjOozAa0l1QOJIGJ3H45kMqLv87maWuAbjL9QfYiU3cdFZoegW4XgxiU0WceQeTfU4S3RZQATbZVXy0+QE0nWaD6+zmCMaJe5Y/hzMtvfS1G/cOwR1O4oaHDyAgm2jj4r3isUnhDBcC41wKKT4PEQKkfgsykoC+ONvOdEZ/xo2wYJCiM4I2wNbbqFuDzpQC5x1ks4eKvQCnRcaZaQhwIsNhXyf7+YaN/LQE+Hf7Lv45SvyA/8vwHB6UTs34ns6QAr6CPRuGzrignGDTJ095y6ZRlgnwBcPiZVivAvnD6FAeFl3KQCJijaKMTnVmaUMolZmIQ17kVmjE6qiIrU0cxCmrWkmcAfQK2aXrQtjYqCCe1vC2byh45MiEPvJg2AeTQYZoKpS2eyk3wll1M3eLMYfYDJX+EZJ/oVvi0ajY6SpBS6kBTieCRqsMh4ltf7/u9lTEUb0yqPmLBFiEzbF0CbBgMrL4buoBzI7lBp0A7+uY/DA91MvB4tVTHqMSAkuYADt02zOzLUdjvaeiY4RJm6wmDha9Ec5K7K+mm+5fAqgQNcg6AbbPEYNcRFSXQBBJl1OvyI7FgU/8WKG+0AKnYbup/VwrNFIVpglxGn7+ziB+90kBjfnOBTXCOW1sP1sFDSe7azBwzEebkHtrmBtDKq7id8Pt1JbLqADv/PET2HGgi/7tt9JR2qx1wcEBw0ambTWcZQWg070BfCF8J3LE8zfPwRBjFeAXhB76f75frwjTCvA0+1zXUPvGWJVc8eVgE2R0j02/Cn88qp2jA26rBlbXMMeWhw8vDl9yol+Wqtn9JP4HM9FLIF+VQ1eYhZRQLBPgC4aleVd6heGvkqj+fl7yBxSncjIIi1aEdTPw6TBGiVF20RNglwW4tI3dSIjlDHnYraufXDbwuQ2lCvD29fFSVXCPro0s4uftLK7T6skt+TQ4yWaGFGOkyGwgN7HpSymyxsGoO0QYkhp42xImwGSgo1eAeRcjfqE4qfRPfh9pTiEw1LAHLKkaW62LV+IzF2SFVahkE4dcNjaJABcb4IpIxjIIulgFjwwKPTpJWYowpdm62yzZaSvAsgqcGmTbb3Gya9oSlwljxlJEBWRoGX2Gwz17ClwRSeRokyBpFmyyGvGNJhW/alPwwnoFDWF2juw0nj23Aky0vhyPVXwfGrwa9evdLhyf+Ns8ENCLB1Zewf33bqY/n+BH8LunR3HiUAoHHs1DURjZzUGGN8LI1PNCNzr1ZrWLgSEj23FSJzsP7Lkovh+7FjlRoxINXuOpZ/AJfpi6RshRI7ikiJSRp5aDMxFgrz7VQhwgkFbpjNN0+KPe07dzJQenrji7Va/+PnFCA0mlXwwgPQOiXye4egtJd90IMNI9EX6xTIAvGJbunfgVQnWdAbe/y4et1xvmJMCTG+CIA0QluHRiVgJcbBISFjEBvmEjR2/OJwc0qp0i2KGb/xfhNppLFbJ1azJQVODpk+d+173HLMioBjiKXqlLOA3OXOEuWaCJ0uwpSqqcoVo8kmBkN7iXuAcwuxZ4D3u4D4XPPW8P67HArmZGiog9nlHhYTAuPRJM0qmyOTawTbiMtGGJWF21VesEeMogjzywjtvq6Y98XoDTuPgbXGeCkGTXNOlVmI4AE5zQq/1GD7umafHPwjr8lxq8WUY6yLXqsJMUuLkrhcTxRrGwEaCRt+AjlRpu8wCX2ABXULeKM54+lwDr8ofd/IHSS5uNPQtygigOrgxxEa5jbP8/J3Qhk1Lx7B/iiIe0UlTxQyKbih/iYvijcBYXE8UKsDBmoVHxDoRRlxtHzCBA7JlIRstzCkJcqqQDjhsE1Om682krwIlCiQBHwzM3FPeFgNODGu1ZuWoNN0n+cO/LIH9YCBTXBEfgnBxeTPQAcgFoPwTkMsDohdVo/1/G4mRYixjV9ezhVVErwOU998J0uATYnSIURcPwQH6SA0S7uXJWC5MgrQBnFn0Yxs2b2Xo9cFAtVXSL6VdFOFQ2zOZsBUhGFSf7hWlH2clwHPent8HiKlaAJfj8S3Nq3OK1lxwglBlCMIpIpxSojqUfhkH8rosaYMHLqruD0xDgYgXYU63BLOWX9GCn0ghkdTuzoNtJCfDGBkASQdOnzolTzSRxQF0BUbe+M+nXxlIERxpVyf2PJwR4+vcc15N3rQFGwKQ4RwyysRThzDCCpdplWEQNo/M0R8iZ2M55IWbGlwc4fLSLw+2neaQGGdlab+yF1eOYngCbJzSi220D+t/mN0tUjNpOPl0FksLexYUwxE9vXnxIGMB/S8/hB9JeKDM0ZV0oZIQCglwSHDgWB8yn0JgdQVbiIfVOjgYe0h0SpEEzEoKAhmLJdhoNsC6th+LLo2todkedR4/qTdcbeWyo59Dk55DOafiDLo9YLAgbJo4XfwmPvn59I3/7LeBbfwakLpxDx/91LE6GtYhRTs5WbTjX1L6ukT0YRwbzkGWt5ABBJBAdlsCsFWBiKq/q3pmczMMuLb4wDJsJ2L2akd0HD6nY2z5BgMsblY05th9EXfu4r2MGopMI42fJy2FxMwIsxkT4AgY0rlh6XlFml7XkDDBTCEYRkZgC1ckekg59kLTUU+CMutXXUOTc28pwFBiNabRx0mZZ2k4QLV6yzbrDicsFxMdxCcsZwL6OaT6QTWN/phkmfZZDLGaeLzHQ61sf7FiVNLJlIRjlOKY3wrnq9UFtVoDBuHgqwB+vUvC9mig8NHhIB9G0eSdswSgMJphTbBtUewEGKAjPc/Y5o8ch74uZ8Tf9PP5rlMfvIxxOBDkICZXqgC+pmvJldg8kyNjlmKjwrXTGYCK63HlKICwOHlxawPjzLNDiWbFMOzoNCDnOcS+PFWOPwEaGUpcNxFluXbYTkDnaGEfQyzE97yDPCJ44ZEGW51HrmDJjYrKS7jhwqgaPwv6merM43jezvJCgSHRJOM8bd7Jz99Gjcyf7vdwYTWahNOfBeXgo67OQC2XnaWGRrewSxzIBXiC8FRMEuHWdhfYtTNcAR/S/5eSGeQBXArMQYIJxiBD16oFjEaaEXbMOtJu/Y0SjTWykuYnogD02DisqJ94npNl+sAYY2dnbMYOheSKMPblWZO1sv3qjurPEFUuvYmRxmkoV4Difwb++m8O33p/CF+7k8I7dPLY1c3QAQTAaU6A4WHXJN/t9+2WHLyDC7p6fNMFqndAA2wNs6nJwfPrPFqvAtmK1P7Y0CXCNp8wBgngAx8OlAAwSfXwuNPQlzTB52HXN6YPDhcLtFbFpu42aArwSaKyQaLIbQSE184OYTDUT2ym3V4ZKOq3IuSEuDgJs4zV8tkbBbmsen68tu/Bu/yjwwS8D226YeI2k3qUZOVQdBcQSGtVozgfFOGR72eC2qtaAR7dW4NkQq3judA0SrVTZyrmx2dgFiyiDyxArLI16p68z9M2bAIsWAaaDbqh5AcPGPDq5i6frXSi69QovIcBhk4gtPY9AHDbTYk8KeVohJhjkYhNWaBpQ7ZxywuvSEcfICERNoPIU0mTaPo0HcDkO9WhUwuK0cHjXlbr8Yf/ikj8Q9Awq0N6Rh+kuGzLKst73YmKZAC8Aggi4PIzI5bMazBYeLa3mGfW/BE6dxDrnoQEmCMkcDLpHrEOd/KAMVEtUezyfaePKGsNF0VfeuGmi+ltM2jnUXdQBl51OegqcI5Cm7g+nBmZY52yaRAPhRRMz+TZkRMh5Ff5KA1raFt8AYDaYrRLt8ifgAxnctp3D5iYF77qSwz+/XcC9fyXizL9J+PFHBQznALEUhrF4kgJMFh63vN2HXa83zkm0yN9tmpE2+3Ccigo9x366CjDBEV0HbCENK7rOfSkSYL+7zAPYbQWfDGNLE/tb0W7pHGRSKLjYvUNJnt95ffm1Tuy+zoXmtlemgryqghE3zahgrDAzcSANkMQNwsyrlDgS+MTFcS3f5NZQVJa9t0LFJosGNK0DVmxiL173tomfLXZoWXbO8o7CnHG35UjyeqJnwUiLJq97kxdvfJcfqVoznuHtUDRgl/HMZCcIuxu7TaxRwjCiQtL1wpsNXfN2gZCNAiRdU3vIMHLBLc1eCvqECG1wE8eNiORMaLKrkHpY9bePkGN9XYkVmsqp4NNsoOmzTjnXVu+g/3m7mT5acefhMCjoZI5oM4KY8pCKLwHpYYlnNDx5YnHJHwjO9suQNBM4jsPI6PSBGcu4MFjaubMvMzw+iU7hZtIq+k8paN0qYc0mK9pPZUoVGjIlTKQPI4M5Onotl0DMpQEmGMupsJhzSMM+KQ5ZEIBrXu+iGuNNO6x4/OGZKzArVpnx2ju8OHE4hccfPM9w82lgkjRctRYl/W8RRAd8aRuTQfzkGfaaFjfS+5kzkMZzZwCFRNnMhEQYjxg24048j3TKiGx7Ara1Tmzf7UTnmenDJBYjXBpPvYzBaTBWkeMjoHOExx+PKVhZpWF1LYcqF4dr1vH4/f0cDcOQy8MwyGDgFUZltR7AIjE9ezaozJoCV6r+GnLwOhnZGRyfgwBXTjQ8Nm43Y++zSyva0+EiD2ZGgKMmDqsDBdjNElJZ4MzgDB/KJDHmcMNIbgoxI3xuHqHIwqpPxYFvcRD+cqPGysgKb89jIDv7uhM/4FU1HGAvAEETPK/Uo4ZoRSUjMD5Ef73Dy85BYk1s4YF/a1Jx1SV3sveS4Amiw73lLuDH/0ArwIUkO5cFx/xCMIqIc+yZ4OJNeOt7/ZTMEF94kiCtChzCBQEbjT0wV6xARl83RoCfpD8OjEsYNwtYhQI2EQJs3zXnMskzQuZ5iIPsOA3k9e9dJCBSiyE+hlrVBaXfiZg7AumodZL8gUDmVEQNCXhyTohDZjhMZRpmkwXS5itxu3IE1SnmZyx6jBAzG/Hu288tJPAcB6MoIifLUDUN4xLw+BB7Fo1EgXfdPvMxnfrZheKlfN6iOan527HTywT4YmKZAJ+H/CEcLKD/tIaVW0TUN5koUYhHlZL8YXggR61mLJBoug5B3iogKlnxmStCWOtX8S+/J53x5y4jmCnAZsyCTFxZyrSCGy+x0QcvQcMc+ti2dewG6K+8sM1kO1plmA0ceoNaqdGFoNgIV3SCIF3y0GOQXYE07t07x8WfCKO7gmXIZuNG7Lak8WLWTvXWK9eY0XtmaeienFm2/UZLFi5dDrKvQ8SXfycjT04Iojn7G5EmEpk8HGzmDMjtzR7XwzAWAQEOVE/ozkmT51gwP68UOLslA5KLksqREIjpBzvFmFwzHRwAXMxAl9fYYkJP59IZ6BiIi0OWXdcxLour69j2klkOVZuBGGaSOOhagV1oBx+RcPs2M77zRFlaxjxgtrBlOl6hxkGPxO4roj2PQSoNEGclwG/cyRLjCNxkYPhK4B2fZdfWz78CS/8JvJZItg08/irqwteMYVzuAN7MD+EXWT/w/b8DbvkQ0LgWeNNfwnrgIWRCbDre4MzPywKtiJDuYWXot9Jp/lPRMPY8HceNt3hQUW3AeEJEhTeHbSsNeOY0+4zNaaYSCMKVfu72ICUJeE9+HNsNHawaTaYg50iBIxVTUjmFoGFEiy2qCjABkWTUwkXt0LquNkLsYwS4R5dHFEFkEB44KZk3NRFiqz/LtlyLS6QQLlEHkS8QxXQeotcITTWjtXF+6zBSbM8wYt6feblB7pSKoqCzf7nh7WJimQCfRwNcOCgjk+Qx0JNHXZMRazZa8eJT8Un+vwTF6q9VyqLbFqDNDHddladTx1es4fCrPQK+cq9CG4SKCOZVrNWdIEw5RkaI1GLbpY5JlaCKSglBkqgwBaLEUVJOQNwoLiSuWluYJH8o4kAX0/zVejlUk5m6uAAupWt6/anSDX5GJCJINxjB8So0lcfO1Wbcuy+J+vUO7NjtQN/ZxaNjmw2OBNsvVmsWVQH25CEV4HKcHWaRnO4Kjqb+kUNvjRWARg8Q1Du+FwkBdpMYrDlS4IoWaFY94Y0FYEz/1CWWnX0hDVbdHouLMkK1fbdjSRFgTTPTLZTNRAoVRbN+rHtDs5A8QoC96ygBFkga3Coz8ASRjMyfoRRtEe36QPjlhllh9zOzNYdT0dkHtcVEOMGZpw9z3QBj0raQAsL4CxzyF0vmaDCV7LJw20fwml/9FaxCHF9e64fJacA//iGHLwkp/HPn3bg/14MU6a4nnfbv+hzgrULFjmuROfQg/bjRlUdwjm0ux7HxEK5qjsLW5QL+txpP8N3M4isoUwIciQuAF9jVVIA+aYZdviBETkUiCkp+CYZzEjbbI/DwCSRoGtzMMzIO20T1t+DXoIQXn761ix/HlcoKGLqtGNzphC0rQBbkUgJc6X1yDOt1HXB+nQY7eTaQRsVtN2CHepS+J9yTgANGpHxBcMlx/PLJc+8hIs/BY7EinE5B1gXcmxoAv5Ob0/1hus8uBC/l8+SzyGtIZ5dG8WepYpkAnwcBHid+ZTDi1JE0JcCrN1ix95k4auon639LDXCmLJU/NMi9lPwST1yB53DnLg6v38rhf/6o4t8fUUEajokX8GUWdiEbUnqQxG4HjCaeEl4lw6OySUDzSvO0BLih2UhJcPEhIxk4FPIvXedkEEn4BWsIefDQ5O9L59gDb1MjR2ORIyes1MRbtcoI51WablMzWw9HnOi/OMCgAFke2ZgJn740hu8HrXB7JaxYY0Z6pqnlxQJBgj3G9o/dlEFTFTsGXaOTq3XFrPrGSh6WmF4lymiQrB4sBiVwoKqMAE9j8zc1BU7QK8CSRy75bc4GIoPYXa07fsR55HMaqwKvMKGn4+UhwW6fiKoaA04eOb+Kez5nIcUjpJ0Geu62NLFj3T8HASZhGLxJhpoVEUm5cLl/HM+Oze/aJHp+QWDLeaWSEoWMgZJZqymLgdzsxP2EToANnhzI0XZkJpOxXdfY0bpOQlq24dknLtI0L01V02Gx4461jUhkj2PUxeRZp7Y0oatjFM3ZID49/DD+lryPzMLc8zXg3Z9HBXG6yOhFCJICN82M3UzIZlV8e2A/7sJlcMtW3MSvwe+kY4iE2HUS0psJd1Xp22624XIb8+KNBEVanSQYSwmAHdhk6MbTRAecnvkCq3XykAbYICXo1oDJRdVFgX4uClVQwCcliAfZ4GTUEoM65RlVaoQbNiNqElAtKjix/nLUWjRUKwkUZAVqiA0GMhUhjA/247AuRSyHQRBQ43JhMBotzcIdnjmJeM7PLgQv5fPFzy7j4mK5CW4B8BYrwGPsJtbbnqV+rqSRZ8tOO52CKuRVGoFc3gBHHCA6zQE0g9nbnBnkcdtXVLzYrlJJwZ/fJOCPfyvCYQaCMuDVQxTEpAhvhYh1m9k00QuPxzHczS6kptbpZRDNU5ryLtTD8vJV5MEHDEc02k07FXvLZBB1BuZrq7pzePb0PE6xBLPHyesVrnC/AfVuYI3Ipoi3XmabV5IqqcC3vEINQsSo3qRXiCyWFLx2DoqqoXvs3AowAXXMKORKXfJO6ZW/2Tnd4qTwFUIU55sCJ+lZ9XMRYCKDKFaAeRk4dYIRDFLpf7lw9Y1uXHuzhw5eFwqDoKGgewCPuxyUADf7GRnsC85yrWWS0HgeqRpGBKVeG27dNP9zlcwCFeF8hSrAxcZWp5SZNga5HMTzeyik0copgTU1QYDJAL14/5rrHHtJsLD0PaTjMCbDeF36LLqdE8e8oSKBT7feSn/+y0oFzUb9vhYZA379DQQS41Bltn5WZ3ZBGmCCDFfAr6UjtPFrs1qL9UoVIuPsOgly7LrZ5ByjISqkye0KvQEulJw4j0az+vuM3XM6QVQ6hFIFuE+Pll9sIH7DUTfT9BoPsca+AencPhXqCCEq1HUkmrSi2mqAsv212K4y7d2JUwOlGVbFm8eR7pfHym0Zry4sE+B5wmzlKcHVNA2RkG6OTmI/jzKyegkRk1H9b56+TlBqgNNDMJp5VsbsCwk40gu84WsK3vufMsZiGup9HK5cwyFY4FChhyiQUIirX+umjXedZzIY7s9jrF+hzRQVAQPszskPXFJdblzBlkka8S6kDKLo/vDIEdZNOxUTgRg8vCLbF5w3h6ePsWrfrCDNJ6Rz2s4eTsp+EcmMhlsbM+BkhRKz2tbZiTwpIN/8Ri9ee4cHjin75WWBzQUpqqcwOdnx6w0CeXlypax9hO2n1ioOmQQJw2DnkmMRhGEQlxGCVFIpNVuVezvP5gFsqGDHmUgc5qoAk2AUo56U1dXuQz6nwl9lQNPKl8cpoDgoJNfQQtHsE6mEgWDI4wWfHEejn/2tf4bmv/L40jMVjJSRTn1Dsxl+aX6kymSeOKd5gaMBJC8nrEZA0Qc7Pm1uAlysApv1wY4lQc4pdjI1rzRBMrD1d17Mhj4qGSAj6lFc/4evwa5kcdjrYgJL/R4dMQ/g0SiJJgf+pbGsSt1/BoEXHqE/kkGq1aIsSANcRC8fwVMCM4d+nbwOygjbhyGjiGxagIFXsbWZQ2WVDa2GYXpvHdUmpEejnEQdI7YYuqDpQRkzocIu0Iopwan89OEXiwEDVna/J+4xBN1qeNo0PV6PBE4E7fDWN0FyuLBZZY19pw4O0lAN1aRAs8o41bvIvCSXsSSwTIDnCZ/eAEfiFuWywebJI3pso8hNkj8QlFLgTMwCrUliPi0DZQ/KR45o+MMRduNdW8dRCYTLoFfIcgKqfWaaKvfc42yqrJAFRvSnz1TCQFLqSAWPVKX7u9l3TCXJ5wNSobhhI/v54TL5A2nMu/3tPrrMYgW4rZqDR2IVa9GXxXOn53FjIhIIAB3eKvZ70oTUYwWQZ+TVPkYmm9bP/qAk22kw8rTbulzH+nLB5HWViJHJy6bizkzThN0zRqzjNNhMHLIqCcMoTDpXXkkU91v3mSwUWaOVutnOH5oCV2yCq9RJ/xwV4KO9Gh3AWXRiZFKdOLo/ufAqMPECNZ+ft2yxmkpmVxaKeu+EB3DEZUcNRmGSOOQKGkZ1D+vZCPCeQAP9X+y1ostpwntruQVXgC+Gvn8uNBK3rjg7PyxcHpnZXF10HOhVYXPrcq60BtFkm9SkS0AaiGcbZF0QCUQqhjtkpl844bHDfk8dHF9ZDz5swCrDKXxqVACpF9zqAQ5sUPCFOhVbrRp8oVApBMPEq/OKQZ4OTwud6OXCMEHEayLroGQ0qDyH5Cjb8J2rDbi8jb03ExYxbJ64fykch1BBxFZDJzSbTuhngI+3gSvwVGbTG53DE+wV1gEXoYkqOnLTOxXJbjbiyA/b4Pe4sFEbhonoqCMJZImPpB6BTEJFYvHFp3dexuLHMgE+L/3vBAghHuybIL3lBNhdJoFot1Si2RSeVitYdFRYV0cqwGSaVYFmYiybTDETghCLTBDJng62DKIDLkfRk7i7PYt4VL5gHeOk+kvMw4cjHPbqPqcen0h9SWsbTPSBRhKSitP7Zp3M8e4C1QfPiQTbL2Efi7ccz5qwYVxFx/My1lh1Iu/mzgkdKYfLPUEIKiovEAGua0P+w/+KVMO6Od9qcdlLcgBbLVvn09MYsxPf5O4x/ReDWiLA7gK3KCzQCEYH80jqcg5i/TcTrBYRXIrtd29tqqwJbmYQnftQELDqyX8OzopDe5O0CkyOW+PKecgSzDbgA/8EvOMzWCjIQLVYfZyryW86VPqE0kCHeAA3m8Ml4q/OkIxWToCHa/zgDAU6uOVGzdi91gSBliRnh8M6lQC/vLMczdUiuKTuYzzPRZP7mtUqQ5MYObEbvdRnur6Z3R9IXxDRNV+0bdEJo5SM4BaPhozAQU5oMJ5wwZABuCfqIIqAaa0dn+3jaKV1oxX4bK2GPRtU3OnSU8bsMvU0HjvPoiqpZhIpRBp51KhOSI+wlDbS7Eawa5WI3U1s0GwYKiBoYfs5rM80jmRFOMQMGvyz7ydjkm2vqS4NLbZ4G4d7clGoFvZ8kqvTKBSnTKcgZmIEWBuyYGVmGDsUNojZe6wLHs1aIsAWbbn6u4zzwzIBXqD+N0RKtFNw4hB7+JOH+NjwxNygB7pGyaQgLlrQbI1NO1Va7JgmBFjvkQBvY98j7HXh1DOTWSTRHhcrvuVhF826rq7rbAaJmHLBKkVvu4yt7wMHDCX5w+XXuag0g6AYW7y3XQ/HiLLfZcc8R+WEHMh5xIkImhi4R+yQVeDSDhkjXQUYOJVWdos2cNOh3Bv1gtm/bbmGShuSbdvnfKvPYGJTeoIKez07dmdnsOEsNsLxduKTqodh5F9ZzR6RzxQlAWqqgLzuaEEGOtO+XwB8khmcxkHgFdjdRPqj0YbHuXC8Ty3pgIn2OZtRcUSvAm+7fB5VXZefRdf6apjH6wJQXkn1zNHkNx0CjWbweghG1GVFs52td9dcBbcse59mtSFuZxUvQ7cNA1UWvHbrekS2vXZWGlxpn3zPcLzMFeB6l4Uea43XMC7O77FB7mtmQS0lHjpMPqy8Zh29b4xqNQgjMD9f45VbmJXZeWqAr0l1gNw6DliNMB2c+B7nMTP4sIQNW634tzEeVft5vLudw6/GAaLYSOd1ok68jBV1foP5GUDs8u4Tj9OfXUcrqJlDKM+2e3NtAVdUswsnGwY0jkM2rGHoBLuHBxPsfZv0pMWZwI+za8dQmyH2JFisSMQVFJrZ9RAPzDyqGAa7TsRRM1YUBtHIxaGoKvYf74avRIDzEHLLBHgZ54dlArxAAjw+DQFuP5XGoT0JPPFQpEQQieG5WWUP53GLEQ4ujQpT0Spq8m4/NajRhqkKBwevg8O4zMHsZlPKjn1+fDRxFd6d345Ncg0MKvMcJpVoUj1paGE3aX+VBJtDpCScyB/icXZTmE9q3FxTn5et4im5efCgVCK8Dc0m+hoBcb8gbhNEByzneRR0D+CwXmmbFxIRdDdVosCpsMkOfOaMh+7DS/YX4BbZtqxsnHlbyh+iF6wCXL+a/pf3VM/5Vp/Gls/Z83DpTVHTSSAIipVym4eDWU/9o2EYxomp4VdihkMQOeQyCu75sIob2rKzVoAJWZZ0lxK7JUunsYcirMI9F/Z0a3DqkomN/UmIZie9fsi5S66zyiZ+/t39RZureYJUIIsglWAyBT9feMxkWtZaigOOiTKaK9hAoVTVn6MCDJMVx/PjJR3waY8J76/IIrrlBsBTOfOyp2h+K9wXpmqqbL4WuYq6Od9XIbHBKWcrYECZ3wAzGAcM+Yk0OP+6G9G6nskgRvkV8EnsdZdnlu9rXg+88S+Am9+PBUM/T+7Id9H/HzeYYTrCdLRpQQavcRAf81F/5euvsuL1lwn4eZjHW84KCOzjcfcQI1lk/Un40UvFKX4UGRTAKzyEMRPGRAmpnBEmUYPflEVeFRDUSbHr7mZc+uRmcAkRI3m9Ec47e6iRNqIn9VUuzga4IuSChtDuQaSuG0HfiuEZ39ebTdOZUBKVfERaSV871TmERCoLb5EA+3LI6c+6ZSxjoVgmwPMAebh7fTNXgMkMzrOPxXD25IQNS63mAgceIq+g1+Eq6X9HoxoyeW7a6NAJGYSGd9ceQM+1dvRKSfDg0Kx5cXN+Ld48shkNigfd7ZlJrg/F/3u7sjSEI6Fbcr3UhrC3XMpOkadOAWMxnlYKifSB4NCeJO1qJkS8vslICXAiyNaDNCcMFhZARONhpGwmHPXoaWLBZvxwjIMhD/hk9trGttkqwBMPUaJJdr9UguCtLnVdyw4vNMPsHfuePNtPkiNLtbOZvEab4GarAHsrOFjN7DjaY1mglt3kX0n9r5IswGPn0OCQZyXAxEZM0D2A7Xa2DSQgZT7Y3w2sumIQFmcW7kgaV1m2I5fVcHgfI4n1q+eoCJZrf4kWeAGYqqWdTeIxFW/fbIKm62CTViMK2ThadA/g7rnszIoEWBBxRGWVPKnXCpnj4Rd6sDo1AM2ja+BnkUD40jqZvBAEuGUDlOvfgZEbPwhtjkq6RZ/NIvHdg4X5PzaUqIxCA9ve6x4/gtoIa/T6guN32Glh2i/3bBXgWhaRTq+N+VjBlMPqhKAquJVno5NwrBJ8SkRayuEpVzt9zXbCQzXd2y+140tvEfCuK3R5jOKAL1tLf5ZrM4jrMyIvCRwwzLNZQGnAghGrhMT4xKB3JObGsMVASa8taINBFalf7ignUrnIJvvMZNGgCTRxjyDuWXzxvlMRVbPI7A4iTh5+M2AkpoGvZQPlgRSbLdhzlGnwygnw2PiyA8Qyzg/LBHgeIIlYpDqWz6u0+jofbFdYs8ta/yA6rZVo1gnwTJWichkE0QF7tALibRX4XnMYXzc8gUeFMxjnUhDAY51cia6zrEJHKrGElBbtv7rOMDJSlEAQr1by9/OBwAN36gT40T0qbrNn8GdXmak3ryGr4F/jEeyKseUR94nBMNDdqcs+PDmMZxaga9V1wC80sgfxKjWAz3RYsTcBVMbZTbKmauYHZdGzltcnku/+axPu+ysBf/dGDrvazqMi0sCqv0VoFexhOBNceoXI5MqWqrwzeZ8XCXBtgIPTyN5vi+WBy29fUDDCxSDAfpHtK58kz+oFXFlrKDlA2PRtnqsBrtwdQDLKuOxdZ+jvlw6LqFTt6DytR4r75zhhLS+FAAvnRYCJTpdEjJf0vy4bEB8vhWDMWQEmg7gCq/bTQp1UAJcTIIyYcLTCgrsGH4U2SwXYoq93XYLJa8hsz4Wa4VDNNqibr571rUKOkSsS3z2Qmz/BSgZVSnTk2hRMWRmOXzQgoOax0pmHW2TnmNM3C/nWmwap1KWiBguC1YErY6fg42UMKRwcncyu47hhCKPGBMYs4+A1HrZnfYjIIjoyBjrgFzUeb5A3QgSPXFsc+VVxRC9Qk9UQz6b8ScBDyCxCGpkgb/KohCGbgZLjIrheMwo8j/GCgA3GfvCm6YsKdbBTiYrizKNnEfQTzIW4XqApOs5MBxJVbKhjg6fsMwrkn8ZxWY8TO+QGWKEP2D05nBlYJsDLOD8sE+AFOEBMJ3+YDjbNgDUqe5htrelBu70OzeLIrA/KonE8cYIo9tn5CzFg9Q6qH3tW7MKjBkYY6lU39RomNw8SkLF2s5U+yIlbRDFRi0zZkakmop09XxnENes4BJwc7X7+W7WAv6tPAZvZtOLtPVFsNWi4Oq4TYF2KcfSYrpvz5DG2kKqJboUWrPTgLD9Gq95b5Ua8o51Hpb7feYsI5zQqAULwi400TUZGMiKqAVubefzJ1Rz+5V0ZtM2tYpidAPtnmSbmeNj1bTXrXe+nZwnu6BojkkINTisHu5FVOAQZMLtqgLZteFlBrJUkY4kAb/brTXmiAk7TqLMG8bmeisoaQ6npz+TNL6gCnJOBzLiGhi1BCG0KSW3FLeomRMZk6qMtGbnZ/WEnSSAWSIDLfI4X4gRxu59DX4UZhrOMfEfcNphSY6jRnanm1ACXVYE1iw1h3QpK6rHhpNeMt4w9C5ObNYFOB0lf77oEO7+FaY7JglGnWw8QIrH9JqIJOecttV7gm+8RoKYYSbUZshjIzn/KeWxIAUQN8Tv7oJgLEEfM8PyhBqGEBo8ubXL7Zpkp8tdP/FzVjAXB6sIdwb30x5/nXDB2sWN3QBvAu6/O4Z0f6aa/Gw56wMdEvBi3Yl09hzvNrQhodqS4HJK3DIDnNARjF4oAswqwMGCmWl9TcCIBzdefxJBNgtg/mQATjKZFGHgFTfXTu8WsMTJts1yTxmndanExg/TNDPXnqHxwJpDisGlVGOA1IK0h362hPtOEm5Q17A0kZtugYWgRJt4tY2lgQWWEj3/orfj4h9426bWO7gFccftd9GejQcLnPv4+3PKa3fTnJ58/hL/+x/9EKDyR9FNTWYF/+uxduGzbBqQyGdzz+8fxj9/8IRQSj6Zj17Z1+PzH34/WlnoMjQTxje/+Er+877FJy33Pm2/CXe++AxVeN06e7cbf/PN/4/BxNq0133VZsP43WIBXteC9uZ3o4cIYpEG252KrUkerB357GFX2ODqcDbhKYuvfMwNJKK8AH6QjeA0V+QSw4TbgxQeAyCgG+Cg1VScdsHbNiJ72DNZutmHXlc6SAwVJ1ioiEZdptZY0ws23cj1d89uRwyreLgE/aXQhK/IQxvP43nMpfCXP4z9WZGEkHWs2geqQzxw3o4U8UN15xPVq1bwQ17un7B48L/SgVfVT8/gnsu0wjOVBvpRUaa5ey+F3+ybvQ+ITTIg+aZZbM55Bp82Ee08I+OVpGZ+6VaAey01+4JjutjE3uFJ1jOs7Ba1+NbTZdJJWJyzUdYOD1ccGBKcHyTpyM97YSWAEWSdRVGiTkBCX0NgzhlNXvgE4ewAvC0iy1F1fg2H4NDy+u+lLm/0yNXoWOGJnJ2NclmgjXJL6uOqbaxdgd4ilCrDJny/zAJ5f9WlsSKP+uZtuPotnezegJmvDDjRgbDiFmgZCyCWMjs7QdWRxvGQJhCsrI2oS4dcHt3PhjRsN2DNshfEgY7z7t61AQ/g+2tAVTWnUBWXWtMMiAXZ4qYvF0ZEwroIf5l4LIpfyGHZyaDWLODTDRzkTW29NkunARBN5ui3K+TZmkSbCykb6I59OQCVV9S3XAXtY9K/bCvz5TTyVBBglDt/fwwiwU8xiIDr/67qjRwa2alCdMpJ39sPxoyaEXqzEX50Zx1e/zDRCdqsGQQCVbp0jdXGUNb9VNQFHnprfgknFWDLg1hC7lvrH60HU4pFAFH97Rxa3bSfnaQ6G6jDyQx6Ynq3A4M3D2H/Ij7ZYE/3M496T2GUTYeFVhM7DA3g6DAt6wlnQBC7HI6LyeCG6DjlRxG2hvUi31cDRN0GAzSELMgWONcK5cljVwOFpxukp6qu8uOKSNjTuswIJwFxlx8aAHStvO/dk5AnhliRkCwWo05m5z4KL8tkE8PrLZv+s4pNg/gsHlKCCSw8cRCJmwK9GbGg2W5DdFSs955axjPPBgufRTnf04s1/+jel38uJ6+c/8X5ct/sS/Okn/xnxZApf+vSH8L9f/2vc+p5P0b/zPI8ffevvEByP4Jb3fBJ+nwff/PuPoSDL+PK3fkzfU1cdwI+/9Tn86J6H8JHPfBW7t2/EV//uzzAaDOOpF9jj4ZYbLsfnPv5+fPpL/46Dx87iA2+/BXf/xxex+9YPYTwSm9e6nI8FGtH/XqI2wAYj1qWqcMDYjy5MbnsnjRVbFVa12FXLbFs6rNVoEkfnVQFuqODwhF6kqgh1AU0CcPltwO//GzlORlhKw1ew0ipwV3uUEmBSBS6XPxRBZBCUAJ9HBbjSBVy7npGZlj4Zg1YJB2pYA8svH4xiaJQtM3OWx50bMzjqt+K2NjsCvazUKldlkG1PL7gCTB543dw4Rrg4KjUH3ZcDQab7yqg8rtko4Hf7Jt/wGmv1xhFRQROxpFsD2L0SfrFPw82bgXofEJjdQnMy/LV0mt1X6MbV9l/iebwDQ7NVgB1umHXyZ69iFeBTQ7OTQSKRaPJz4EUFuU0RWJ7247JnjuPUB28E1l8OnHgOFx2+aqpJ9dfoASQZGRZBgzSqQbVo8EmKToAl9HXnJul/idJECLLPWSrZNvfMoHmeDgdOqGjcJGDTmkF884bbcNl9Z3C10oq9HUeABsBPKtKH5iGBWGAF2KpraVuiWRyotME3jySyXTYNmRoLbPfVUPP9Qys86G3046Ykm9XpmmeccUkHbLbhjDaIq8gNuMdKQxmO+SxolLUZN1k2smu4cicPez9xlRGpvj8ydp7Vr+pmeuzJdec58BBCV70N2HkTcPCPeM9lZODIw2Fm5+8zp1SkQwaazusmKXCJ+TsMdAQ5rOA0ZDUOheYUDNcPovCHWmyPrMLpUzyMnjxy4OkgNly0wCkiUFb9XWgF2OpERSGOqnwUssrBOcQ0pB3uIfzFVvaWj/9IxZ5gB96D7TDu9yB3SRgHf9xIp0UPiH0YoU1nFTALGrrO0wN4KpJcHkkhB5tihDBsxqjVgPvbt6PXVIGdtoOAzEEc0sOMoFI5Bqmaj+jX2NqayYOP11+9GY01PmQeiUODBqnKgeaACATOwzVjEYLIyDgLUKiNwHa6E5f5NTwicthws4THAkwzn1xuglvGy0WAFUVBcPzcyqfdZsFbb78eH/nrr+K5fUfpa3/5uW/g6d/9J7asb8PBY2dw5a7NaG2uw5v/9G9pJfbEmW585T9+gs/++Xvwtf/8GSXC73rTjegbHMUXv/69UoV5++Y1+OA7bi0R4A++8zbc/ZtH8It7WVX1U//wH7h29yV4623X49vf/9W81mUh8OpVovCojNcoE40qN+ZX4b+k56nPYxFEu0oikDkhh1UVw3gmbUBCNKNZJ8AzTZVG06RKoaHOy0Go0CvAo3pFe+0u4IX7gcgIRg0JSoAbVQ8e7hlhU8a620KxMa6IYiPc+fhsvmknD4HncLxLxTWKhm+v9NBuQKLTHOqfuAk/GuOwmdiy+a2oG2iBqkmQq9LIr44j8+JCCHB4YkqeA54XunGHvBE7lAYci3fBWZARk0SsWylB5GVqk1bErvV6QpUiozaYA6dqVOtJpu5H9cqN37kAXVwDm2JblX4KlZ4c1mt7MOh7g05oz30QChUNELvZ97tqyyvAM4PogF+zETCYNWR2jMP8nA91w1E09AbRe/nt0E7vwUWHLiWo5Jhew80x+YNhWIVqITMfRKtwrhUakT8QKYAYMULiZVStis0rBa4cf/O8htuvVsFX8/jsjt/ge0evRnPPGFoONgHXDCBQI10UDbBbJ8B1sTwO+zUoIo/ra3k8NXN/Ef5frYpjPfUwDpuR4wt49Oq19PVmM7sPds83c6CMAI+sbIJGAsKyItUBH/cpaBpOMCeQXPociU9BYutNqpFOSUFcE+F0vQQCrMsf+MF22NoPILTxWsAdwIbrL8GXbmElxuN9Gr70WwXPntHwWT2cwSIpSKcn32dmA7Gy3aCpyOpqu/vT7WjgJXqfPPW9Frj+3ymMSszF5VwCrOt/BzuAmhUAGYSKEtNTzwWrA6vSzIbluVE/pIwBqlUGFxiGJHDUiec3e1TkuXH0cRFaULD/TzP4ggiVhCts6IApzNaZhGCcTwrcjPtESlECLA2YMdImYX28Hy45TfW/4oiJukSkkKczfm2qH+KAGcM1Sdo8uNY/YYXmsJkp+dWSKrQ4ob8a+IZO3PPI9Csr8jxcZguimTTkGbx3Z8Ir9dk3XCog6rIjLYbxfZjwb8jgfQEN0QB7pgmKOmnWcxnLuKgEuKm+Ggf/8APk8gUcOHoa//TNH2FwJIgNq1fAIEl4Zs+R0ns7egYwMDSGrRtXUdK5bcMqWkEulyEQacI//81H0NZSj+NnurB1wyo8s+fwpGU++cJBfOETH6A/S6JIl/Xt7/2q9HcST0w+s3UDu6nPZ12mA5n2FaZ0jBkME/6z7lEn7DAyKxuSOKY5sFNrwH5xYm59R4HdtHdW90HkVXw+VYUKPg67kKW6z+EoD7cZkMic3xSc7AfqvICDGJ4HVQTUNLgz+6C1XQLuijsg3f/fGBUTWJuqRKPmhaAJGOjJo6nVRMMLChkOhrLvTSfZjcHlkujrxWVOt+yprhdvvYwROvm0iiMVFnS5TZA1EfsOiJOWQfCdgwW8p9YM9QSzpEq+boiqy5VYct7L1VIxFIqRwpIBZ/gxJJQsHJoJ/eO1WJPMIOYWkRNEXNYm4IWzE59tqZfQQ0hutADiuR9IFTBiN6C6xohQgj0sq1yT981sKDSsoTTXJbMKXwWGAIMRkq8KXORctuPwrgCHAWr473LnMJ7QEEvNvt1F0uR0qNA4GdlNEZgPeHHZ00fR+67rwG2+BujYO+exmgnz2eeKzUXsSBEAO3/X6A4chmEFqpmDr4YREm+FYdK+I/vVch+rqG1d0QOTvYBYWkM6N/9zjNSzvnqvir+6i8eKqiEUbhRR+B+gKulG4kgSnk1R2CzitA+3fLkEwmiGZHWAy6bmtWyHjf0tk1YgxgpQ3Ab8xRoR+3Rp0tTPNho1NFVbcfpxpul/TOhAqpLJwFY4UqXK93yWLWdTNIGXtzigNaxBsDAC/5k4TD0WpKqzaFIGIPqqwY8wbWoRLuIXTYdfGky8BrtZBdJAk0/CYCcjFAs9Twp1bfQcFwfbwWkqDC8+gPxr34vbLmPT7384ouFD39GgaTw2b7NCeJENSFQjuZfojifz2OaIqsGaURA2i3SwfuhIAceMJxDI2uGOW2B8wQdcEYbXZ8RA52RiK1c20v0ldB6GQgY6VifEqibwQ51zLlu1u9GaZqOagyEm9UiuHcflLeQbOexpJ+cqO+bPcV2oz22FWBChcRrid/SjqdqD8X2M6JMQjEiKh0Ff1HzP8elAPhMSkmjMeiAOWjCyRcK64X645RSGXQaIXZaSVpjIJQgBFvrMyO7iEZEFNDmSdBAXSQEbW9ms1MjxCJwQofhzMFmGcPhEaMZl++12jCUSKJyjN5l7vV+Jz17TxKG5zoljKTOC65xId2RAggRfID7YhOenlVnv6y/1WJ3vZ1/JZS/l9c4v8Px4WQkwkRv8xd/9Gzp7BuH3uakm+Lff+zKufuNH6e+EFMcTk826g+Eo/CR/nRAJn+uc6nGRDFf43MAZ9v/U95DfHXYrTEYDnA4bRFGgMopJ3zMexYpG1qk/n3WZDnaTCW7L5C4rd6U+1Z9QsVl3dui1hBGRMtgVa8TV8kpEPBlkBRmughmNaTL1pGFbTS+eShlwytGCZokRqZEIIb+sekVuCFPRHyLTzDlU10ognXDVRh7VRx/HYOtWSoKdx5/G6Bj7Lr9mQ7Pdh+HTKiqrNfQf11Dj0rdNA+qzbggpVknyeowTf5th2eXY3CSjoSKNVBbYGVHwjW1M93gQu8FVDKImOTGwKHke38s6tD2tIwjVZsApHKqsk5cz23I1cOhRZDotW1lVBzEVxdlEEFsTdbAlmlGRPIJ2N9MB37rNhL4x1gzSElCgkenhHFA1kkdWBeqTeUqAmxrsyGTJPsii1iugxjV31C5pTOmrX0XJgdfAzh8nwpCQg7uxDVZtsuiSvk8j+ooB2pFsFVScGhNR47LOut3RFLnQU6jwAnxIQ+ayEEwHPGjrCsI/GkVo1+ug9h6B//zSfmdddhFhtw8xaAhggP6+wi6DK2iQgho0A5NAFGdAiucPCcCoHa+g5vScpGLrpi46hT0SIfvXNq/lFnHfAPC+9hi8Kzn8Q8PP8IFtb8MVewdheMGD3KYoVq90IzRwbsWox+pgdXhSTeJ5VNQ2wxjqn9eyLVZ2y8tlORpI43cDolvCp+oU/E/k3M9+qiKB59pXU+/fpIeQFGZlBk1FWwXbP7GkFX67NPf+1mT6zDYH6pBq2oCjQROuO3MUpl4rUpeGUaGG4K5thi07+d7W6tcbLHnS1Ep0uGy5jX4TztoN897fRWgcj15SUSWzJhFWJa0eOIHB2CheX8Ou7SePW1DtlGhB+kpLDY3YFSQZMatp0r1krmVLvApbWgFxURvtVFFpd8HBq9glduF0zzqgl5wzYVTWexA6M/lxNFDVCDvG8aadh3EqU8BzeCscTWvgTI/Puey4rxJt6WHEsyakx9nAfLh6HG9ZS+7nGva0i/DbmdQgpykIhpKoKNjQUzmA5qY4ggUJG3fYSvtdhAM1rsnFkYXs83KEcqlJThBt6QFUFBJ4qlaCpDfAxa1Z5AwKiMJO7Gf3ktG4AI9XwRWrLNjfKWLLakbsM11ZOGGjDXAkpm/q8ZmK813vV+Kz6WweuxwpHE+Z4G804sQaG1Ymc0joBCuXINr7ucT3r9w2v5LLXorr3T0+jySlV4oAP/HcRHPOqfYeHDp+Fnsf/F+qyc3mFtDwtEiRyGaRzk/eDmcTuSEZERySsTbDLrQDWj9ki4rmhAcB1YHVoQDuN57A+jyTR7T6RuAwZfGZ4yLGV/C4VrdAax9R6Sh4ptHwi+3A+6/jUaE/WJ28gmD3afAn90Bduwujm66D8bEfIMgnUaHaIEV4HEuEcOzU5O3YXKjFNYWV6D0WBG4cgcGiYTAanfdI/BMbScWJQ+dxBe21DkTMIhKaEwdwJTj7o4hGJw9QLinUw1gwQzXLGH0tETlz0BSRLnNBFQCiA3ZVYFgTwUejGNeSWI9q2AtWcF1W4vVD7YB2tObw6buZJu6dV3EIy2waXAkXcCDFoTaRx94qwOhS0HGcvc9lVUrrMxtUUnUymoFcChYa18kxH2htFGNWzznbrjkqcNNhRr5y66L0YXmsX55zf0docYmHzQZU9hUw5OWQXxOH8aQTb3n2XvzhDesxvuFSpJ+8b8FVk/nuc1kwwoo4rFyCEsqAVIA0qOK5OI+NFg3+eJ5WHYkrQ7gQRyZFBlsG2J5k1d+mlhAkr0IJcMco278Lrfa872cafvdZHsbKAm5fewbje20wjBIZAA/BkcdgNDl5f0sGaKIBrdIgEmNRDLvXYkww0vNlPsvmjH66raOxAnoKGfhX2Kkf62thxFC4FafUcZzghzHOp+EUNGz1OnBvRwWtDD7uOIUh6GLyZAy1jez82N+Twlhi7mUrUXZzTzWupyS6y84qkBwhgSpg12IYNzkQm3KOraPJhlZYBEaEnSL732iZ/X4yE9RAAzSDCcimofT0QrAbMJyIYUvnT1G9IYKEYsSvD+WRz6Rw41Y/7I+w6vc1DadxRPRiMMo0+fPZ30OkGDAkISkJeOzFKIS0gp+0FeBVcjjdA2T79G33YNL1SY5xwelHK56E2aiiRT0LooqPuiqRnMexlnkJbekeHBkhVVIOhcYkgrkwqj0a8jJwqEuc9NmfivtRzTnRHg3ipxkBsslDB9t0P3MqTgzGS7aGL7UaKlqJWaPGfLSTEmzCMCpTUfzKXAmnboF2Kj+CYTmOG9AGKcG8gYOKhNXePNbUpfHoCRHVlawwkR9glXO5JoNsjp/xPrcUK8A/ex5YVcujsSaHbtmEg7CivlFGPMoI8PA4uUfEF916v5LLXsrr/XLjJZlJkgprV98QGuuq8PSLh6nbAqnUlldeKzwujOkV3WAois3rdGNzHT4PI5XBkG6DFYqgYkqVlvxOvpOQbCUShywr1P1h0vd4XaXvGAtF5lyX6aBoGtU4l8PlYweFP05a30REkEYPwqjhXHhIOoX35HZgo1KDI4UhrJMZAb6kpofGae5JaIDJVtL/doyqKJDAeTIFqSjnlPsP0545HrV+gPiak7qFoshQn/kNsHo7lJaNyB5rQO8YqRbZUKO4cIw7V7xIEuMIqlJuxOVRWB2TpxamW3YRROp34yZ2WlQNa/jROlY1fQ43QoYBXEUttLLP2jQjrigQ3wcgfe0osh42XRtVLecsY7bllnTArgrIVidtCc9DwSG+HzvURgweqwWuHKIEuLGaQ4NfRucIcNM2ET9NsGN06owXkZSEN9SwKrkvIOHsM3TSGX6nNr/plVomo7EOHYLYPKEb9mEYI766c76j0dGGwNk4lT/w20KULJ8YINupzbrdear55qjm+30DY3hSs+D+VSJaTjrhOSHhNdffi8xWHr8+bkZq6PwFiLPuc7MNlbr8wUqkKjxgHFLxWIyDwovYMqLC5VEoEbC7ecTiBWxBDYSwEQWLhusDJ6Do0/PdYyryZQ2xcx5rHfuGgKf3aLjiUhFvXPsCvm68FtYcT71Q/dXpc75DcFjwKeevcJnwJHJmA+6MfxWy3TvJQmCmZZNjQ2cLCAFOKAgmSTXfjg7RgFD7WvjyJuyGC7vRApMpjrXeETzeza6l5OYQDp4MQlvJZoHc6X54bGzbzw4rpcXPut0p/UFNdKzk4T1yGKqggc+IEEZNkIQYOGfFOZ/3WNn7DafsuPt71djyQSIeJgM8sfSQme/+pqhm1d/aw0fw3uQuxLNZfF/ag5tdx+i18ofMZiTX2lEz/BjWn2kGnxcguJL0vvYAahZ8XVcPpfGXoTROyhz+YY0GEtSYURIwCAXk8xJNRXNWFCZ/B2lw4nnUKGfpU8ppzkHU8lQWMa97mdmO1swwHhlheu3s1gga9NmbfZ0asgVu0mfzyCDCZSgZ/93zKj77lgh+POJBUhXAyQqy8rnLWNA+L4PMqwhyKTqLJw2ZMWI1IIA8kJAoKVagoleLIK8qGOOS1JJNGjRjpIENBne1aXjwbBV1IBkYCaMizyrVhdo0okluznU63/V+JT5LXOL+4gfAqibgyjuBUykjtvZoSPs4KrMbCsvz+s5XaptfyWUv1fVeMj7AFrMJDbWVlHAePdWBfKGAy7dvLP29paEGtdV+HDhymv6+/+hprFrRAK97oiX/il2bKEk929VHfye64vLvoO/ZuZm+TkAa5ciyLt++ofR3YoFFPnPgKNP2zmddFtoA5+thHp3HhOFSc/+gEMMhnk0fv7WwhRJknyWBWuc4Pt+v71qLvSSBmMsrdDgKqh8VBQ55vWnLSxZPdKdHn6G/R7bdhD6eEf0GdfIggCCg2lFNp+SJRaIIYcAEUeRg0Zt/5sK2FmJZwyEc1XCw0oWCwGM4ZoN7rxm3/fZFbBzjqS63iBvkNpggYYCLItQ6YQMQW0gK3DmNcBMdzC8KzEkjGfSASwmIkCYVDbh+PY9LWzkYdXJgjgNDXZuRHd0AacRIrbysNgEJmW2300K2a/7+v67wyUkvEwJMm3CmYFecrSvR8FrshTk9gKcLxDDZgNcPJfDjB7rRZwiDUzmIz1XCyOVQvYVNc84GQuzOCxZHSf7QbGIDRaVXQKRvK54/swnZDkMpEIM0wpGO9DVDrDM/vJODj0shZWUL711AA9xUfOQ3KpQ8oHg5tNVPxAQXvYmLIE4ev/jTHG4x/RFP/7EBew95sU7qmXcjXDEGmdiIDcTVUtNVuiOAZN5EPW5bPGPgORXZrAMH+luRSFqh2go4Ut3DYs4b2fnRpBDVOXkAk2THBTbBEagK1FMvYNjAznmp24qEkUetwzxjDLL8YC1d166H2fbK1vOsmNS10uvj5he6abCOW7bg7fmteM0qdoHcl94Oftdr8fqWZhjOOqDyKlat6KLn2YCy8Ou6aJ/+3RWM/B5JAXecFVFt1y3BBswQBYXGqZfgb4CAAqrlIdh+VwPprB0ejLGERjJDMwcMFiv8sRhiWQut3icao9jdyB7IT5+c/Vy9b78Gg6rgnZVhXOtKwJ2df9PffFFMhBP1RDjaAKdXf0e5BPIcW1dyX6Xv67dgWJJYI1wtsGU1k/t1HBmBGRIgqlD8WQyOvzobwhIRDd1nSeQ6h5/GbEhF2TURX3aAWMbLRYD/7mPvxc6t6yiR3LZxFb73r5+Bqqj47cNPIZFM42e/fRSf//j7cOm29Vi/ugX/+sU/x/4jp0pNZ8TF4WxXP771pb/EmtZG6grxqY+8Az/45QPIF9jD6Ef3PExJ9d/8xXuopvfdd96E119/Of7nJ/eW1uN/fvw7vO2O1+BNr78GK5pq8eXPfpiS8Z/f+0f69/msy0Is0Li0gCqd6PQbBvGDNRI+stIO32U34tHXXYqMQYAE9jDaUt2Ln4Q4nC6moFnsaBLH5heXWuYHHNX1ZroDG/DcvYAiI1vbil7SKUe68TUHTNrkIj7xzp2EM+ymSryA54NdK9l6j4yKOBSw0gdl7Om1uPnBA9h8pBu3P3IcH89fjY/md+P2wnpsVGuoN/ED4kn0dE08KDK582Bl8QkrtCLCfJpaopFRh/mUHSrHIa4IuH4Dhzt28AjLbL+7j9to9DTB4LgPFSn21DW7JKRzE9Zus4IKXNkMhTPNiDevz3tSAkyIVtnDl3hCrxrJ0in1zM4QAiZ2Dp+hFmjzJ8Cyi6PV11oD8KTGppctB5zgMjy8VbM/7FeuMeOjf11bSgJcOAFmFeA6Yw75oICfPb0DFXk/1LgfP3xgNwyHXVTo3FgnYZtSD2PaSNOmmmvZYCepE+C+BVigTUU4yeG/HmPHsXkru1bEbiuLtNaT6C5v4/DIZ0Xsasxhz0k/7PfVwvqLBlzJ75k3AS6GYJhlFQM5DrGITH10rc+zhLCdDZ1Yu2MA/tVPIuo5jBFpFLItj+Qtg2jvSrJzY8u1bD3DexdmgTaVAHcdA9IJnMjrBLjHhohNQDMdW06+duxWAXzIAHWcDTz7jrCBr8zzMJrO4zqra8Pmk2dQHePozIVqLSCgOPDCd7YgFObxVI8d27SDCDzD7iXPSp1YoZPVQWXhpLvc3OEPUeCqEzyeS3KodLDr3TzIzl3iBFFCoIHOTliPOGE65IH1kUp406zyXfQvng0tBgXhFNPOqu48hoMZXNbG9tXTk8e254C4vD14SKNSk0scaYQvUArcdIEYRAc8YtET4HStb5H00p95nQAPWJARBSTHOciahOY6JkOKndUHrlVpEleIjsH5W9QtNRx8gV0/aosVnRY9krzMn3wZy7ioEoiqgBf/8U+fgNvloH67+w6dxOve9QmEI2xq7/Nf/S51ZPjO1/5aD584SMMnilBVFe/6f1+khPX3P/wq0pksDcL4l//4aek9/UOjeOeffQFf+MT78b633YLh0RA+8cVvlSzQCO77w7O0ivzJu95Om+ZOnOnC2z/8uUnuEnOty3xA7MNIEpa0x0ErJcNcHH+7DrjTSm46nfiw3IO7LZfh/ss3YvPj3TAIMlb5B/CW4xMPJd5iQ6M0Nu+HJSHAV64BMkRK0AV8KKChL6eB54IQ9n8byeo2/O/KNoS6xuDTrKhT3WgXGPsQNA4bFObDe7q1BqvODkLqtkHBON2WyOjcN4tdrRytsO4TmPQhcZ8Flx9kzXTH19bDGU2hZjCECs1G/xEc4PvpDd3YYcK6zey1bEY9/wqwt2qS5dhpcRSVBQesJxxIb4siXBCwrVmmlZCjOd0O59QEu+2M+NCQ6ELQZkBFpYTxhAKLUaWpdjMFkZSM9gnBzSThFMk5bUdLLIt2txkVGAZHqD4JxBhgFhQ7eSaXiLcVoPryqDUWMDquITXPcALiBUwQs3Ege/vRtSrefDqI4VgcVbIDpr1e+HbNbvLeuoYNcNrWWdA5xQd6LnBWG/xg5WpfXsODX9uKUMqBJHLISQV4CzaM3r0S9jUx1O/qxSqVSV1SVwTx3qEz9OiY9ZmKnpdQASb4+oNZvOsqKwIbo8DPQaeGUeDwvtcZ4cqpePcVPJ3yPRy0YPiwD+Qs4/ICGob7ASdx1J1/DLItr6I/R8d2UJ+302nntE3ElW/6HGSDBHgPA/d8HZV143jTu/3IZVX0PaAC7/kATf0jYQwtEqmcC+gaPU8CfOxZ+l8PHwax4pD6LIiYRDQnw3iCWAEWrwW63hwyegIdgTbuhlUdQornsXOVgA5WjJ4f3AFYjBxuemwfvf1Htowi2xpH5a9aEOt24tff2Aqn/Xu4WqwFn3Iiai/gyVwn6jR2nPvPY2B7LMXhGqeG741x+HAXIXDEkYWDZGHPDWmQncOuSiuCJP+WIFCPGnRB6mT3EzFkQmW4E6csVzE/YP0anAmtfBrBJLuHyYEspHQeZgOHkaiG00Nzh5b88nkVb9jBBkzBC2iBVsQQCcQoEAJsoQQ4J3ClBLg+nfSWk2GSHEfkGaFxATAS+YOA0VAMjgTz4s7XsGu/q/MirOwiQWikgN7OLBpaTFBMQsnrfhnLeFkI8F2f/pdZ/06cFz7zT/9F/82EweEg3vnRL8z6PS/sP44b3vIXs77n+794gP57Kesy3wAM8RCTFGQtg3irNQ6FNL5Y6rEj3Yv3jDyNd2lP48mWNjRYwvihVoHe3ETaRY1bhZHYXMkchsLEE3F+FWDVw974ocqJB6wq70NOPYDNTa3Y6zMCQSsuc3lg84YwntTgHvfTjPS4WcQfr9tICbBl1IZsnptXGAaRCGxq5HA0ZcawwQDTETs8B5nm8dlLV+GpjR7kAw0wPXI3GvcdRIvqhQEi/iiyqnp/Tw6yJkDkFGT1yNYFIarvt5aNwAf+EXj+PuDkHpwRxnBVYSW0Hju4LI/TIR7NdRysJjIFLdBKaWZgQlbTG/ViR/wMUMV0wKF4DnUkDGOuCrCe/obeU/C62f5aPZ5Fj8NIs4qdWhhRIoMYOAuzJmFTgVVh5J2MRNYa8zjTPX9C1K7Lt2N2HnIWWGECnt2g4q+OdwLhzTDv8cK7q5uR8tz05JYQ/KI374IgGeAyJGDg8hBTPPZ8dxPCo3aofBY/NRyAyS3hi5wTXSMraWOe7/Q6cBoPxZtDdD1Q+3wa4yRsSyRaSg3Dk40LFgySjveNF6vx2at6YHHlkI4Sn1QLVq9P4UYP0xjc/ayKu7OteN2ZCbcJtROwbrEhNY8EOpderbYWFBAraxJa4z7ABoxdl5rheeqnGLv67cCKTcDma9DqY02/PR1ZqLvfTMkjYuPAY3ej+V3suzrn6wFcbPJMx5mPbQcb0JNBNUl3Izrg5JADzeoY4KmcRIAlqwBD+wQBliDC3GNCqjmP6zaJCyLAhqaVeNeBX8IQtkK2FPDz7jNwjZrxkfeewvh310Doc+JDlQZII2baqHXPLVfgyqeehZM403IC+hcQg1zEp/o4fGeMzIqR3yaOU8rIYoC1MRO9ruuaXWg/HGWaHn8dapXHqRSmiLqhBFA7v0CMNjWBsRTbZ0QasNLOzqGn5pA/FPHcWa3ky06i4C80iLZXhgIxKyCSsSBlzcEyzCr8A7rEjSDIJZGFDJMsUq30qCShkGK69JMnB7FBZedvoYkUZTSMFPUmr1Lsey5OCXARycRyCtwyXiEN8KsdRP/LRyVYhu30YfD/WhnR+XbNa3B7pAVXnhBxT4j0yQPX1J1BVUUM/1R946TvaHYy4tITFkpdxLOhmAgnejl8P8jhh2Mcvj/G4bujHLquMCN+hQHXb+/Bnbey6sl2hxf3f1rEC/8g4c/bmEZ14+5+HKr9ODibBl7lqbXOfCQQ25o5qj9+OmKllRfLb+vBg8OBLS149Ko1sPSdoO/L1jTgtDCKB6ST+K10FFmO3YRkzoh+sAab+MD0XpSzovMo8PSvgUwK8NUAt9wFfPDLGF2/CVGRNKjwkNrtGNI7gAlGEwLVKZK/kYcKMZBXVBGWPnaT9FVKCCXYQ7dyrjAMXf+LvlMI6FPvlhYVlTn2UPERP2BdB7xNqYNB4zBWZYPWlIBZU+EVFRwbWAABHmHvrXBzuLqdx4MRYrkEfGPdEHgpDT4lwXbWBEcri2adChKF6x3wwPOlNXANuRYWeGJxwIMg1VW7ftSEcL8dVkMWj9v3IsSnQAp+w/ZOvPWa5yFXZMGp7FaRunoUAWJCSkiCxl4bGAfK+t/OG//5Ig/uURF1bqYDJilpx8Yl/Pw5FX/6PzI++RMFay1piLoFHkGy04HLrO3UP3ouVDnY+hrzKhIKh/VaNUwJFpAQb+mCtfsIhKfuoe8xXHs7Vm9kRPvUqBfYdj37kge/SwcjzQFu4RIIOQ9897PA9z9XCnMgITpRH2PR6nEPGrKj+gzIBDRJgtSrT49XM3kQd5r9Xt8ggC8L4pkNpBfg1kviCDzFqoZPiR1QMjlsrJPxhm2jWPeBo1BFlZJfgiMb3RhaUY9/WcV+/6/q6+is3UJBKr5MEjb5+uvXVDhNaeLLRtPPaqv189dTBUHiUTcQovZzRVSM6j/PRYAlA9pyYxhJswpwwZ/F1c2MuD95cn4nKpkd+Pr9ChIZDY8dv/AEmBz3ISrtAsQhKwpBGziFp7MvEZI+U1wPDhgq6oAHzOjjzRhKs4G3+4zK9L/ODPKtCZg54tuMVzWGB/IY6M2VvLyJc+YylnG+WCbAs8Drl2A8pj9YzWFscGYxYHDjc/W3wTzUjn0pHm9t57HqEI8vRL24c+2fY3TFLqYl1dFsY1WOrhkikKeCvC+V1WA0cPhKisf7Onl8oJPH4RYR9lqNPE1oUEHMwipEoR47eoZ4jI8ZMHCU+V1uu7obXJWGpjb2YCUyiPlUgIn8gbgs5PvscPysHrzG47gjg9+/bhsNgDCO691dM8UC167EE7gdT6SuRvvB8xCFairTOv/nXwKEiKQTtBqm3Px+nFrFqh6kGplVJsh8hhdhOMGqv8S+qptn5Ck9SLSrGkuDS7Jtn7UCTLxda1eyn3tPwabrEW3VGrwu9vCs1AYBfz0EjacJdfStu4z0uV4r5Gnh6sgCCHA8AzolS1Dh43HraR6f6+OosfL2SlYeJolrFS0VM1Z/zS/6aJe+6ZB7YVVgiwNuOQTnj5qAEQss9hxev/UInrNMVFdfTPBoVKLQ7jpNiW/yiiDya2O4bIx5x57R08l6Z5OVLASJGPbmW9EkssETIX0FScSnf6Hi/oManZGp6mfHJWVgy+T7rLhMOjgvHbBPD8HQsgr1rr6CX0d/z+wKwqWn4fEH/mUzWZoAAFeUSURBVEj1uWulozQEZzykoH/Ln7IvOPg40HOCHucmJhtemASCrniMVYHLcJToy8m5fYLE9wZZBViHRGKEh5yUHAm+AvZvYwPMQgcjdzlRxEa9uWs2kHyfm97gRfMhCXxaRMRUgMnYg65NBXxxFxvQdKXG8DPxAGReQcyYxgPjL+I9Q09goxxCWLTi7xvvmCzjeInozguo0XXAZPrfZdPJaaAeVeiFSQ+FMIpssGAZssKoJQGnF1p5GMpUWJ00BGM8xc7lpCWFdbUcVFXDM6fmf7x++YKGVR+TqWvExcBgqRHOXPL/7Sfyhynj9KIOmMyIjNqqoGgizIUkWsbZeeLYOUKf5MZXO/vVsffZOD2WY8Ov7mr3Mi4+lgnwHBVg41HGmm6sZd3yH1v5LqRGBsAXJqb4u3Mc/v50DA+bmwGzlcV2EhhMaDayh3nX8PyGquQedlKP0V1Xx+6EG+o5fPo2vcHrWAXcfyjgyT9qiCIDTeXxzs/b8OHPBKBpHIKWBLx6JHLtBp1IdNvgmEd1cGcrh5GsBMfP68EVBLRzQfxmvRkaz4MLD8NQJMCkE1uYxlKhrg0pOHC83UgzCs4bZLr/+d8D//GXwJOsIndk5xb6P5kKlgUJ33pYwT/dq9KGEIOuEzzJj6CLZ9vcH/bCk2L7PKgTZqIBnhGkqiQZKUF5w8pR6mPMJXlICRE+M/uetkI7UFGHdVoV7DAhZjdDWcOWV21lN+NT82yAm9oIt7KKhYF8aZDH604R2zY2YjJ02OGtnL7BrcZrgdhnKRGIqimuCbPC6kBDXxDiiBm8RcYdb9qLozUNUAMTDUYvJDlKFP1CAZmrxpC9lj1ot6WyIDkeiQvgADEJ8TD2OlpQ72KDO7JtZAaj6AaxZqMFhjO6LZ+/AFVUKJmrDfYTv8I5v96puykU0irWcnXw5XhkzBKy28NwuyfS1rgHv4MNGnGdBQ5bXgu4/EA0CDzxc/palYvYBXLIy2Sa/KVv9p54GJqtQGUQBbLpZQSYbHqhkzW9FVYDXc3sb1qYyYFiCo/rN85NBFautqDJZ4OZJK8R0m04jbvbFJglwKHb/d13QMNZLYR/ER/Ht7RnYBjvwhfb76Z/+4eG2xGRbEB2crjQS0EXJcAT5I7n9e3w16OW6H+72HW9o7aL/k8ioyuDbBZKI3r9mWB1oGo8DFkRoRHvZDtb58O9Gk1QWywYLFZ2By0lB4h+7lwtUT834Rhh4tgMgHQwBkGWqGOEZwO7XoT/I3LYwd4c7v7uKB659+UNTVjGqw/LBHiWiomvYKPTrRynYp1/GA+YmvFb3yXgu45Oz1zJFD7Bis1lFmijCyLA5TpgQoAtRuDf30diOzk8dEjDT8Y20b/d5lbRSxpoiDOT6sEmlVVIU74kPF0ZcHkN1Wv16sqgGQ6jYU797+ZGDgODdvBJCZqo4BfSISgV+nRseBgCqV6RChCplvqY9mwS6lax//sXZjU3I8gg44Xf04fucI0PaSlPE6nUITe++oCK3xzmqCSCk3lE+STGpDw6jaxCNRh3oz7C9nmSE+esAK+ytOGTX/kNPv+1B7Dhyevh/ce18P7LWtzz8d04/ukdcPywCf4nOazqHMOlGhvg7N3RikqePZxrzAWoslaKOJ4vio1wK6smyPkfYhyel6M0eYtPiWhIytN6nbUoPnB6c5KQkFDnXED6jsUBLzHZJNrYFVFU5hJ4wrWWdt8XEZKZbjOQnCBYXEaFJyvj4ShQ4ysSYFwYyHnsMdbAZ0nCKOXAKzydGifhG8QjfdUKR0kKcNIcRdTJ1j/RYURj7eQEx+lg1W3QkikVV4jr6c8vbKqBTC24eJh1T+OW2hwcfBxpzYoz5svYhx/4LpBn0/8tuvyhN3hhpB8FDeDWsWt5YNAHp3NCz05CITm92jvW5kTMZcW4x0aPO9kXMVnA1esKMMyhcCKzA5YnAvRaGai04purekES3ju9PDQjBz6jYUWEMSgiaSpwKj5Vo6ESWZw1+PCfNboE5AJWgLvyImrsxXuUBcQ620RsDSsbUJfpKpHCDZX94B1Zus0rupgThFo5MwGusFqQj7MBulKRQ5WV3QeePLG4KqSlCvCIiTZBlirA57xPb4QLGmHKuKFlNISeYYPiZ6QOiCQam+yT/OLavouJSEhGLvt/Z3uXcXGwTIBnALFfMp1lD6KV3jGovIz/t+4uSkS46Qgwgd7YgpWbziHA3fOUQBAc75sgwF+8U6B6Q+I3+td3a3iYdHYRuYKYxLjERsBblTrqyJCHjGvqRukMmjSuwubNAR6NPjhso3Y6pTsTtjZzMEocxkgyE3koW1IoEC9KUu0lxGecuCAA3FhfqUozCaIBqNa1ef0Ls5qbC3SZHIfjujua4ZQDqytFmpBFpo0JjnAjwLv+BtG7vogwl4Gq8bB3sYdEQe8Ynk0DvClihC2dox685SAWb3JWhKHLBtPzPrz1F8+iUrYgLwBntnphE9LgNQ1VhgK6hjTICyRExUa41srJyz2aAaoq2PGt7sjQyvNUVI0zO7wiAhknHZvMCxYHnEHWGOSpSkEaVfG4ey0lH+V4Ls6hKjRhdLvCk8fYO43Y9edG3HbJBZZAEK9wzUnjqJucRXswKyVvzW1mOPod9PiMVTjwaVs7JDMjT9EOJ65qmdsBw2Bm50Gqz49ASkPGKOHF+H5ExhnBt+tV4E2XsGvg2EgACtFY7nuE6sKLOC/97xyQV7FjHezxoVUrsEEmtfOyg09I1K7sZEM9lQkVq8BEpx+XBZBEX+IcMxta7Q4YD7NK8jtuehaNbTz6ZOBpn5521qPg200aNlnYNtUbNHysmv38qX4RBXL1kwFpMczjAiCq8hBNcQicQgd6fERC02ovJH8Vanti9L7lsCThNGXhDDCyWD/ECLg2CwFuswmlBjjZn8VaPVlzvg1wLxfCSCPLF+ighBQdVKgY0qu95UhxefpejhyDIQ75PWnIWQHumiSMLaOQJXbTSSUvvF3bMpbxasZLSoJ7NcNTIZVG5U3uIP4+U41eWzXtAufGh4Dp8se7j1OvXkoa3QEY7DbUCgML1goWK8A7VnK4fBXTrv3Z9xXE0jwKyQz22ZtxSaILq9xhYAQgGXUEZ4QR/JUeuhEPiTBVafC3xDEWdtLpRBvRAc9QiN65kqNF7OQQ+7ZxvUGj2JBDJBD0/7E+aA1rqE4PJDiqiOoW9tCOh9l08QUEXWb9ahxv8WH7aJxOg6/bIsHpkmDYzx50Jx3Zkj9ol1OFJ0pCHUjlLA5B136SIIWZ0JxjVm9Xf+gYHpfTGA9Y0TYcxyd+lsI711WgqsaDQp8N2oAPUlDFs5tr4TEzLWylsQBB0/DxXyz8ATRdBZjgSJrDuytGMDAUgL1dhNTcjEJx8EEk6UYelj5WGfQ1xxDqcsIwaEWgyoAhYnEwBySHBcYe9rCtdscxOiDgtKUaCDh08zmG55I8rhnPA7oyosZYAHhOd70GbRI62HXhiEUincZJSw3qXeM4HapiBHibgTZwGfaz7c02GPFxWwTHNAn3DTRB7bHhsqp+sMn6mcHrPsDcABuo7VntRe7UfQiv9cAXMNC0u0C1hKpaIxRZw7FfPgc4B0nCyqTvaQ6cp/53tu22pGH35iCOG7HhdC/2EdnF+BBqNEZ25ZYEOjJuINiFrqYALtnfQaVNKY1HVuWwuYnDAxNOkZNAJg/cwx5KKCvXh7Bi9zhiMEDJarhWL4EcOa5iNw/8sk3FjmM8vtSgwcQDT8SA35PGhJ98iTWxkUa+C4jOvIaALY6hhJtWgVevJ44IYRhJ9DkZcAVCCL/WgMCjUUTaA/CN6TruqqZJ5ym5eu644RLUV3ngsZix70E2ILL4PAilLsf9SQ27d5N/NNycxq6StCrS3LxQvJTPT/2s8BAH3YobWgWHP7tdr7RPgeUxjjhvQuksQD5MhiMcttzahVChAlmifSAWaeELe2yWsYxXO5YJ8Ayo8EoQTzACnDOG8a+Vt7M/dB6Z2XCJaFf7zgBNa6mVUoM5RDu047IBocT8Bftnh0mUoEZlDwTffkTFi+0aDAIgRcdw38qtlADf5E/imZEc7DoBtrv6YYWMDlMAzw5peO36OFrWDmNsn5MmTdn8ApTxmRvgiJ4Qeof96UwcIA1RFjutOnHhUcBmATfWP30FuL7tolR/CbhRtsz+1mZoB/eCzxrQyHkhpoy0eqJZMxipn5BkdNW5sS2aR3iUVLziMFp5ZBRmm2YzAckpjeyEGBgjhLxyeGgsg5xNIzF6SMYU2q39x8Ec/ux1I+jebMYGYQgf6HgbtUz7oPBf9MFDSOH3fq1g/3k0yxSdIEi2id3ETPgJTqQ5tDrH8Cghq0MW1F1mIbbQJfzJFj/4JwVo1gLWX9eLJ/5nAx2wVbbNjwC7nDyEIDvWlbYEniDNeKQJkRxvmsTHyPxznnWoTE3MeKx5NoXjQzm8u4O4D4BqKuedhDYPcIkI1QHf7DpY0gGbjQLq6kRIP2ODndXeISAHtNrGacqXEDXAn4lCmkPmrhh5aplnHGdyoAOx/fT/8RC7Nm1uDusvYcTr9PE0MkTonGLBJOVo9l/4CnAorMGwPgrxyQCqT4eZDnh8CNZsBbEJBtcWx1DHMJDLorvtUnp0qDwrIVIZRJNfnXU2Sxpk29VSGYTlpIzBagFuF9uO0SiHtzwr4Ok1KojD1MOrVWy1gbrWfKKHMGQOGNRDKC4w2rMc1QETAkwawWo35DGidpV0/RXXRlDw86jZGsbpPwLWoBliLgvZYodMztMokwfUVHqwcyPzqSbIRMgxVSH5zUgVmByiWm9cXEzIN2QhE1NqUoVvNMLun17vX2jJodCZhbw3z+QvvjQat47htpgDT+b0mZiR87CeXMYy/g9jmQDPgFrRRbvriQ7ziUwScosua5hJ/lBE5+ESAW6WH2MfoYbs8+++yMvA2SFgbR1wsFvF134/8XAjBPh3vmvx99334DoX8HNhHKuUaowjhddXM3b7i8AudJ98Dq8l1euNo3gBqyCOmuFtMJIw0Wn1v1uaOPTkpZLFVK+WKMkfaNWbVn4IAdarkKQCXI66tgur/y1DcZlqZQMygQdh6a2GOeSHqrIHW8Q1BlRPxF53r10JHDuBUNIBx5iGuJ9DV0LEWleBpsF1sCJ5CU5bJRDmwIsqnjgbxnXX+EBqowM6MSIEYOBMHmgzQzGmsb6VuC13oUbrQUgV4R3M4l2PMwK9UISTwGBYQ42Hw0OfEfGJHyt0sJPTOIxChuhPQh6zYU2KLxHgS1o4rNb8ICIBS3MUDXa9CWbUhOrdZhzE3DrNANEXp0XqOOEzJPBETANCzOVCI8c2xMxlO9ddj9hYDy4ZTiJkENAUyuHrfSRQABcFXDyMPf4V+BPrUxCEPFAwQBw2g8vx1BIrYTXhHdrz9L1GUYHiTkMMWzHU7sDWFRH0z6jB1pAjiY2niX4WGPM5EA+1079E9OPsq+ZhJKMkUhHdx/TF06Eogeicch69FAwMc/BujML6ZADikAxrfSU0TYISZdMWYmsC2lOnAFFCZrMRI24jqiM5GLptiDWF0Fgx8wDbHzBAPM0G8w1SGP/6GwV/P6hRzf/Va3mcGbAhIidx5xkez65n5JfgB0GOzkRcTJzNcNhKnCAGm2gF2CFF0DjSCyHsoOdmYAs70WpXJGkkNZEKNJ88grObdyBXUQ/0s6tiVRObqWrvHcUV6RC6QqQngkMscBZ3VIbxnccUPKFrgEWeh89mQyiZhHwe3bov5fNTP1uTdOBq3Tryif4z6P3l9Iba3owFr8WqYjYQwpeO0ttNwBVHaoRpwwYuoBRpGcv4v4BlAjwDiJ6SwO+J4EnRxUzwibyhh3UhzwiiA77u7ZQQNqefoC91xeZu0JmKbz6k4M2X8vjMz5RJulIpFsQpcxXOmKvQlhmGyTkAOVyJ/YYOfJlJ/PAL/y7I9z8MPq3B4iogE9BgHuVQW/BgDOcyFzJ9SvS/vaMG8BFWHRvlkoCXNQqRSlQRRAtM94PJCjh9QCzEbN+KzhekAn6BQSUndJkW9NpjWI1qaH0ekgVL/36U6ECqbiu9P93chiD/PCpUJ7wdFsT9GQykBEaAnRw69KprEZWUAAMOfxodIyqutLHL4mRZct4TJ2Vc3gaMFUR8zfV9uIUYfqT7pf7oXjLdev5E4c++p+Db7yVVPA6//riIHz6l4KskAyQnwVsdxuiYDQ09aep16+ej+K8PCHjoS0z/W+sZgyeagcmTRTZsQj1HpDlzS1Bq0qxsK3hyMKcVPBHjgNE+RoD9DZQAazY3DSV5LteKt50myWGsKnhf5CKSIloBvoRO29c7w+gOV1IZBB9jg53xZgca9PhgAoczjHTYilC7E1duMuEnj0z/tX4LB4XnYOpg7K6z1gGcYuX28SDTBZnt7Hzq686WXpsK0mymJ5Ff0ApwLKpB9eah1qbAD1ixLmVHWiXWbhzkQAYCuR31HGfXHFl2cwDVB/ogdVoRu4LH+gomdZjOCaveYWODHUHFkMmIvx9g3uUHuzUc7yOpaOx8J2T3rk4OP1ipIamAWfJdZJwlFeAK3Q1h2IRsLouqTjKAc8DXEoNBkpHPg/Yv8LVJ4LQbbT3dlADny3Txq5oZAT58qhd/ImbQqdVCNSqwB0ZRbY3g/hcKGNK5pUEQkHXlMRiNIq8s3DrhpXx+6meHtEiJAO8L9yAWmd5nuUvjcD1WQoSAgj+D3OYkhiMiqj0yUmTmjpxDy6loy1jGgrDcBDcNJAMH+xibbm22j6O9ohiQcIY1gsyGyBgQGqJ62OZaJk3oikxjGTYHiO/pO7+tnGOzxCsFqrO9z7eV/n5tdRB/b3gEbYEBGHjgqLUOJxULOpN58CHGnPlmts6BuGtG+QPBMEla0zhohjzSXH7CkJ+QXh2cqgDBoh+wXgUmlkTEQoz4m5aR5QsFskxDhJXbnrFaoRJbsoxErdoUVx7PkmnQYlMMWT+DEWd1WzK+mx3HYGZmL+CVNqYttfizsGsc0kb23n1lzh29I+zhMl4Q0WYaQFYh+5SDI13APbpm+3yxp0PDNV+U8ZOn2TLefaWAhz/LIdPAo7GO1ey9nTIqVzTgvz8owJSxQgmZqMXTGvsYwmN2VK1gT3db0D6vQAx/jD1ozZVpBEMaekjE7Qir+qq6E4S6/nJqh/K8OrHTXkgAo4WLR4y4RBgnrLVI8ga06IEYxO1AOs2OUV0FI79dOk/YZGcWFPluOy5tnfk4NDp5Wj0zdrDzodM5MaqMRWSq+S3i8B5WQa92A597I48PXMtjxwoOViPQUAEIPEe1z8EL1w+GbIotP7OekcH1wwpaKQEGDTnIKQY22AyynoLONUzHTHTAUeIDbeCoPdt0aODYyNhWl8STcaLxnvn4/STE49ZTPK49wWP4Ih7ncgLsMqVhNOSp13Fu0FzS/9avG4fj+QLO6N7a9hqmWa8bYfpeWgEm163JgLoqNirp7BmCkcxm6AlwPoOCx46rJfK72EAa3O4XT+Ah4SRi3MwhIwqnoVdPiOto6adP7hfHzXTAk9ZDatJEsrOMZSxj3lgmwNPA4yUNcLpmjhDgxu3sD11H5vcFHYfpf80m9gDvCl7Y3cyFR/A73zb6800uDQZew5u97Kb/S/8uallG4pqjw+wh71/JSIMrNL15/K6V7EGXHGPVsbRBn/4tSiDKCDDFWO9kGURJ/nAWFwtFD+Jh+wrkWyeYh9oaQcFdQ0kv1WD3nKSvd9YyNpAlEckaEJ3FC7iW0y2TXDK2V+ld8TmlpMclSMYVIEf6tDmECiIGUnpFcjBPX3upIMv61N0q3vR1GT1BJom49hYVVTcnaFKZkONx35XD2L6Cx6m9rApYaEyhMZfBd7i1qK3S/VT7LfMKxPDqDTOu6hSO6414GGXHlUggCElSCAEmOuD+iYry78IXlxQRAqxyPPbbmib8gNvtEOMG5HkNNxnZtfXlQY56EW+zMgJMYmJtBg6eYpjCFNQ6BPBhA/iYATLPo4eb8G4jJCIaZoOdyLiMXp1df/YOAR+8TsDn3yTgN58QcfpfRfziL8QLXv0lyBJOp2nIro2D4zTUBVNYpfpLBDiSFiZsyJJR9NdVQOVVCDEDokOWSdrkqXAnGekPNMRwPDr3lP0DUQ4HUhef/BJ052i2D2qLdmh9VtqvQNBiCULpUHFIH2D6G9h7vOMSeEVFrqKOOoasbKwEz3EYDkZRIWdKARhyIAuPKON7VJ60eLFP6MOLon5PnQX3GY/hft8JvBBmRYazgglxhS8NaDLpxb2dy1jGYsMyAZ4GjXY7teUhU4aiKYZoo67/Lfr8zgXdDq3kATxlyv2lgjgykEahIZjhEIG3+DRc7ZyQPyDMqqWd+oNj7Zoh2ixkjJlgIZWkMhhFYEszIRMc1CB7kA7KRQJcrABPqepObYQrEeALL38owqCvg+pvhNo0Uc4p1IyzCjTBcDcwwEh43ypSIVOQS5so8UlzM1eAPTSmFYiZZbQF2Pv4aTLmx8cYaYyf5TA2wojQCx0XtvHk+bMarvt7Gf/zRw0DIQ6+ggx5BTseHYcrkMlrePEpVhkUm6OwFVR8NyShxhiefyCGyQJLUB8c+ZI4EecmEWA4vEg1b2QBENk0Dp86jWAByKvAby8yASYSCIK9zlYEbDFwfAG87nU87FaxLdNDB3f3hjnsSwJ2Yw6ykzUGdZzxYPuK6aULfjsPgy5/6Kv3oRDSz2EdQ33s2B56gVV/SbPkazay5T51UqU2hDzPlQZQJyZ//KWDhDxmVWh2GT69mm+ACM4sQ65JY4gcgCKC/SgYRITc7LWEbtdIJDRT4fKIMAwxQtlYGcHp8Qvn43shQGKSO3NkgMK22bTfQwNBOKOMlsFxHEkBp/XbT21dHKpJgSgLCAyMQpOM0LzVJf3vme5htFlFBHULNMWfg5yS8dQC0t8WM9JcASFDCsP9ecSiMhEU43CCybAkVX1p4UPLWMb/QSwT4GnQCNZUYPEl0MWbaeMJtfaa7/T+QDtqCv3wC6xS2T2Uu+AEWON43GtlxPOrjRqIYcReKYBus79Usd3fzW78jb4Y5Go2bVidd5yj/zVJHNqjIoQxJtk4LcdZ0lsxXnZqBbhIlAgBJsLD2lb2e9+Fb4AropRC569HxhWGXJlBoTGJsBSd8B8e7qL7nqDQ0IqkgVVFiYevIgm00jedF7ApqhMsNY1KLyO2CT1Eoxz9evTmWFxEn4WRzP6BC289RFwV/um3Gt7yr3Zk7s7BWsvI7b5DK7DhLyVYo4zFB6pCOJ0TMdLfg5RmBm+UaaNYs3UWvzeyvR4HpCBb/3pnFCeKFrok6CHCBm3hHa9nr518AXKhQKfErz7BM6nERQRptuSzKbzoWEFdJir0yiCB288GAs/zFRiXOTyfYOti8DJSN9ruxo7W6Qmw18ZD6tTlDy1VQJmlHMHep+J46p4s2vWdcdNmjqa9kaS+t31TwSWfkbHxkwW841sy/vpuBV+578JPNyfILAPZzh0TrapiWwzEc26op2wOX5cgdVSyAWu+yznJnq0clX4jbSIkqPFE0D66+NKzzmaAGruuAx5n9yDBEoLAabQSfVpPxvS6ZMj1rJm48YQ+21TVjDadAJ/uGkabw4CxlKNUAf7DvsK0uuiljtPHmG3jgQQ7B9TcsvxhGctYKJYJ8DQIZBjB8HsjOEu8Uefj/lAOTcVnLD+iPz6fbUMymrrgEgiC+/xMmuHRWxl/7r2E/aB79h6McBDiKsy8hnwTu2HWKo5z/H8JOkJiyQFihDTAeQIAxwOZFNP2lqNIHtx+Vv01WZj8YAqpuCgE2FWBYEJF9K4OxP6kG/0hBajS7Y+IXyshwaQU4qpAu4ERI9IoxAk81cpNrQALnAg1wi6DzngYZr0haGD8XCIVGmME+JDfirzII5dVEZ6hWepC4UiKNAmFoPEaXME8thrX04ooMfhv5JLYT0hTcAB70IKKenacfKnZAzECXpb2R382JXGqvNNf1wEr1AqNrMBT9L+TGQ57ki/PtLiYjNIZDoI1nvFSIMlVPlZ2vU/Xxr6gE+AVNkYYU512bG1RpgvNg80slKbWO+vdTE9bBlkGEuEJpvSmneyc+PWeibJaKAHqJPCjp9ULqv8tIhJlJMa4PgpNVzyoutwnHGTXb/kMzOkm1gTG99iQkblpK8DNZjcND+HteWgikL0Q0XUXwQmiyhGd5KnbZGOym4PJCa9sl1ODXMfupS397B5X1dwIu9WEbL6AnsEQVpgkxLKMFGr+DO556tXpjXv6GNsPef0RPkjug8tYxjIWhGUCPA0cIVYpanKPo/GqArYbz1L/3/li+woOt1V3QdU4fD78FiA9s6XS+YA6MZBoz5pdIDNhxe78e+quYb/ofz+VBqSQRgmB3MKq0JUZR8lKh+BSvQEuEjWVSFGQOkBMRCCfg2x6gkBsvY79T6QHF7HUIpDqpB6wcVZ36KA/hzTAX8t+IeSXvE8nCAcCjOwTqyhinBohU6dTKsBuEm5CfDVNMrKhCOIWtg86Rs8ltsFRRoBTxJCZLG7g4vtuHknzqCtkIdcxAnRFlDX75NviqE3kcIBwfE3DPtmCeo+enjZgRUXlzI2XdQYmBeBcOViyMk5lpqnuU//l3hIhfjkhpKIYMbrRq5rQ5huFCgU9/BiuF9gA6760rdSQR3CVmZ2jwqAFeU5EA5NIT4Ih5aS2hopZw0gx5GUGkOa3S9vYrfE3e18+wphKsGVlDEDlNTEYVxeQWxM7V9+pN8L1t62iTgdEMtDf5ZyWANco7FpxNCYwmGYDgMUGErdtEmUYrBOFgksDOgFOcdRrejSq0RkBe5XeCBeS6XnfWsWu8Y7eUSjEVkxhg3jFXgDEPBJl44ZXE+JRBYN9E/efuH7uLGMZy5g/lgnwFFSYzJCiRlqNaFofxZrqEfzI/w205eewP9NBbtIkvpjg7uhOnBg1AHrK2AVDKkZJaEE04IE0q3Y8nZYwbA2wpKY4q5p1ZAFO13pam5I0TtVUMCCg2SfpfwlyUV03Z0wjXxaBTB0tpgOxzCJo3XbR7M9m8gMeEYjHJ0OEDzAbtmSUlPDYi4NMBjG4sgkCiRrNihBGTIgUCAGe/J0r3YwtOQJpVGVVhMzipGpcOcKhAhRlguQPD1786hKxpqpJ5pFfydieQX/OkcaoukS+1Ky0dzyLBoPumkB0wLM0wlWqbJrZWJlBKKghVR7/XEaA+aPP4JWAmGLT4XsFH3zWJLJ1T6AQOAgRGk5YatCpd7tHFQ7H04DPlIJiVaiLQHu7m/pnT4USZBXteCMPLTi7gPeO7ey2+PxZFYMTjmsXHckE266EzGPzzh5sfGMvMuSGMpUAE79mTYVqd0OuYedF75EK3aFi8nd6EowgVq6I4VRk+pCFVxrECYKg3sJ2dpJPo8aapk2OhBwTnB5i111lIAZNJPcxAb5QHG2WfEn/S0b2Vj0UiDhADOqSpVcrTh2dGDAsO0AsYxkLxzIBnoLVFr185M/AVMOqgHY+ix98UINHN4ifDXfu4rC+nkMsreGfv34I+OEXLvg6cmWV2S+rLXgsCvxNrnHChk2vxJJmoaEh9uCssqRQaGKSgBaFbeNbLuOpzrE3DMgxtnFRbo4GuCKKcgeev2gBGFPB65XdsLmZxkPLBQ0xe5n8oQidAKv1reDNTDtJXD2iskD9jt1lhbBmM9tuwVfAZgeHqIkR4Og0GmDisBYZn3ioDl8E/e9UHE1xqE7lJztfWGRYK+Kw5FUc0p+BJ/uH4OXTNDxACBuxpnZm72lfhm2jrTKNs6NTKkekkbCQB1fIgT/5Al5JArzHxJjsdncWr/ey9fw9sf/LTMyoEB0wlTxUsmMxeNaN1bWTK6HE9bYwxLQvgy32OaU6byjKH158eatqKZ0AxxUBPlsMPkMUOY2tSzZTti5kkEuuc3KeNrB9MfRCAALHoVZXrhA4XAKMw+w8aFwZwUE9RnixoUhytwSYtCtnHaTHlDTAFR1WzugEuMJYQKGWFRRaz3ajQfc1J/pfnwhERdsEAR66uPKkVxodpzMokM5UMkBKLVeAl7GMhWI5CGMKGvQGOGtlHAUfe/hEciLqfTK++6cC3vINZZKEoBykc/zTt7GHzL89QPShF1b6MAlE5lDdglOuFrzmhZPAthXTNqwd6wOuUDVUGHLoXpmA4ayDEuC95g587Ga2fT94gYdX1/92KQk2LPKc6wE8bQWYoJBnxOllqgBnvCvx8O/uoTd/dV3LhPyhCL0RDoEGjEtxOOCHOGDBSJYdG5IGR6ZV6c8quwSydgWrbAJNW1PzKrIzWAqFRgvw+Q2UgI8OXXwCPFgAkhkNDnsKiiMPgdiBtSZQn8rjRBrI6NVbdaQXJ9c3wl6RQmLMBm925kAMZ5ztB291Ekf3T5k2zyQh/vyf4beYELrQMxfzhJBk09xUB5x5AbvsgInEtxH5AyHAaRbKUZRBfDAAVDkiGIMZ8U4H1twy8V1X71iNzXU1kH/KJCGNzSI+WmsD1urSHR0cx9GQAlFQ0K0QBxUg0KLho7rByFwofp6EG2gLlAIVP0tcZ9yyCFUGnhILkIlmXRXo/eb9d6ya/CHDUUDugn1TM/BCHoWICYPHvWjyj6KXyILIvcxrg3DSQAdFVYEYjgcXJwEOy8RaEGj1jeEh5+N4o5/Z0JVbsRUrwD7iitGQgqHHhrU9feB3iBhJKYgm0rjWi5IDhBzIIUIunlcxCnkNJ46ksOkSO0ZehtmoZSzj1YZlAjwFgTSbI6/wR6GZOGQ1EW/6Xzd+/Z4x7FjJ45/fDnzqJ9N/9s9v4lHh4NA5ouH7T17kEXmRmBYrtTNodk8kgGuiGhxGpTSNXqs68ae7DahwaGgfFRDLOBAYZZWisEVGhdkBeIl/bhJQooDbDkng4bJbkONkFEgjTS7E/k4w2gk4Z644nvPZBaL4+WwuBJks0+tCnLgYqCoqaoiGNwkkBuh6MuSA1DBgsaO30gKSLSANWDCe163QnBxO6Z3ljqQ+yDHk4bPN7ABRToCxHgiOFGgF+uKDw+EUUJ3Oo+uSMCxPBJDdEkZtIo/95V6tqoK98GClK4zjYzYIgzaYSSPRNJHFxnFGBmvcMTw8Dcflh7tgdM2QqvAyQEyxqv1B7xoUhgG/LmceMriwz94MpCaq4cwJQsOVYg/uQTXQZ0Otk8g/ZKxuqcZNV2yEfDKPPDLgKnj4HaTKSqqEM0/njOvSytpKvPzQT6niRAOb0AcadEXSBMg5GgWsFuTXc5D35XHg8QY0VY7hyZPsS1oMLABDqkrDnCvg1OjLqOc4DycInwTUWTPYamfrf7Csd/iMPhHlcaooNLA/VPWmoEbtOKOxKZ037uQQfrRogZZF5OiruwJM8OwfYzS4peggsoxlLGP+WCbAZTBqImx6bHF9LdNTnsjW4tTRDnzoO8CPPyrgzl08ukZU3L9/8meb/MD7r2Fk6vO/UlC42PejItEtEl+P/rTWHSKKOJHmIIVU+BplqO4CZF8WYsiEm6p8yCoxPB+5AVs3GZB5lJGKW9+yDXwFIYovEg0F8MYdM6+D8jT7nyz6/TdfjK2ceZnvfa3+wkm2njcSKzbdjo3iEH1de/0qZE7HIUQMiMVZlbvcCUIIc/TjeSWGmIVdDmN6KMJ0OHUsjUCNAScIK32ZcDjFYW0yjxO7g8hcHqQV+rqjedw/xdJ1bxK4QRzHcdRTHfCqzRw6WL9UCW6LBEFPJmywxqm7w2KDSDTupCrvCuBIGtimc9X7vVugkehZ0uioozMLjOaBFeYIZIcMMS7i4Hc3o9l7EG96DXNFSR6KwAAT8i0x/D7dgtTDvzp3mTyPCrsVn749DYeFw789oOBI7/wHOOTzXqsN46kk5AUashY/G8kkccPtbAbq9d4YojKPZ2J2pBMyHn94ykimdiWw83XUEvGd689A3geEjnnQ1EbuX+zEqCqwE93VlEAhIWI8c/GbNs8Xp7McLnVoWGMGNukSpYNlriNFJwi7TQVXl0ChJg2JND3+Oo32O1l1fPt6M+7/jYF6nssV2VK4yasZZLJhmfwuYxnnh2UCXIY61QWOJGB5cqj2M2HaIZqOpuHpU8Dn7lHxpbcI+KtbOaypzWAowiGR5ZHOATds5GAQORq7+fjxl6EyWKwAF6UKM0gWSIe/GNJQ2SrDa5CQXZmgBDh4qgKj1XZIkhEKqXiSGTQeyJpJ4oEGGMzMTqw4Dc5xNG1JJXfc4hSvwQSQqdtclglkZ8J0n10Iyj9Plkma3vLkYa6y9dRU5kxRDuLdLBnBSzKt/GlBFcaBSmTXjOhewCRBzwQlzi4BSzaIcbNUisadCUSL+fBvX95KGtH5Xp8sMPG3zglqk3nsn2JLtncojDqnnqg1ZEbLbedK/BtsRP8BaPY8HKQqWO4AsUggkIZGAoMJezMSttkKE/rfcxxVOJDsits8GlJ3RGH/pQuJXgfeHrgcNsmEkWAMVj0QJr0yhKPDWeQ6z9W1EwnC2u1WrKnIIBTXcM+TMuQF8Fjy+RqXC4PRKJVBLATln92aUWCxCrAax5HjBWT4AoZiWZzsnGzbhohGrBIAhxOFEz8GV3MJtEENhrGd4LnH6LXiirNqaFVLFMEUaYDLL+oKMMHNbg12AUiXNcARkHtsb1BDQwWHgFzA6JuCkP67EeqwghXPR2BeZYOiNwSr7jzSijZZN72MZSxjGVOwTIDLsNLgpTOLhfoUnF4Se8vjUMeEjuwHT6porQLefaWAWy4hrxMCMqGrKygavnDPyzQaJ4EFhKASD17ix+vwTFsBJk4Q0J0gbnaP4ycrzDC/APQc8yG5kYfbAyRDQ5DgRE5M4B//8yFg2/XA9bcAZ/YDv/npzA94QkYtDiA6Ydx/ocnBOZ+/6s3A9uuBQ48wMnTlLcCJ54H72HqWUN0CvPtz4NNxfNn9W2SCBtj6qtCeCCLgYk4HNe5qgFgw2fOoyqQQMlfMSYBfCVAv4OQEebHlFZgzCo6lJxPcgf4+ZGqNMJjzyGcM4NIOcNzk4IMaiZEiMZBFLAIklMVXAeaVAov8NduwR3HgwxhHUuXxuGsNEDxXk/58nKMEuN4YR887I3D/sAXiqIjsL1J4NHcUb5A3UOeAQl0KuRdm0LSTSYRN7Fq/d7+6IPJ7oZ0gCAFOKsy3esaIW3L9k2Y4gwknQhK2rB9CZrAK+SNG3HL1Zjy27yiMI3pEclsY3WfJz6yyvhhxhs5EaNiiV/tJ5Z808ZaD6IAJAfZDRszhgPFWM3I/T2P7vg7I19chotsSEo/sCBkgLGMZy1jGLFh2gZgmAc7gj0P1spvvoUMsGauIv/2Fio//UMUPnjDgu49p+MnTCvUKfeiwik/8SEHn5LdfPCgyENObnFZsZv+TwIps6pyoURrFLGuoNmbQtCYLzaCgEDfAmXPRZq5CiD04xqBrK4sWaHMl31Fv3tnJ7wVHsYM/0DCRAFfuAFFu5yXnoVocyOeZDkAdUHAsdAncXmaj1uZmGkmLP4sdBq1kgRaLLK4pxfYsYErKMOisjOh/j6ZJoX4KeZUL2G+sRL1Dr1D327BuXVFFyuDXLfAsVemX71w9D3Bxtg338dV4JAr8bb4JOcFwbihLSQcM7AoNA1UqDG81kxxhaL0Kbhxh0+NkUAtRnIjxnqaBdfcaNvD59Z5Xjjwl9enshCIgrcxCgMmsB9leIpGxNeBa2yloBhVaRMVOTzNuXrsWXIEHTDK8lWkcC83sC70YcGbKTMSBaUJXSk4QYgEmzQ1hhYSujYzkG5+uQ+8hNoBVAllE9XvaMpaxjGXMhOUKcBkqSEgEkbRWRUlEGKIFM3o7JnfSkx6u3+wF9pw1YTCaRf6VTFYicgd3AFi5Rf99cvW3iJNJDteFNRT8HO4I9OP7LQHglAtKZwFhQxzSGPOM7VCTrKBdklPMM/r55cRIWQwzqYBNdYAoHyAM9wB1rThbYUdLD6AMy9AUDknzLmxoBZpEvXHPo6DKJiFiNILTODqGMBmkUgOeQRJhNIjgdUIyX1zIzx7OK6hMqeh3SKhKqtifNcBkOPc7SSDGjY4oOkYrYTzmwrY7zDhweEIe4i4wgaWLOECcVBbvGDgZBgL1SNj8uPmIAGxfzV6fhgCTZqmsCqyNRuFRdkGsMcH01jRCPyS+sOzcLrQkUdDMMxLg124GjBLQMaItSPt7oZFK6lZoMo+sXgGecSqf+BlXNmDE0wDX4LPApnFgbwXkQ3lsqG9GAVkI1SIeGrwWcrOIj71b34dlIJIvSRBQIO4VM9nbzIAL/dkfW7RSzTe+hsPHpkzEmMzAg/0cCjwHo8bu1Q+7I3hjUwX83XEMn2YFDNmfQ2RkQie+jGUsYxnTYZkAl0HQeKjWAmq8rInkYJhUCC9C5umFAiGoKzZRkjdjapuuA35tSEXBzxNeD1NzEllCgDtkqJuCEMdYutgQpnoAzzxd/Ipus1xg0g9YGNEtC2+YBOIHXNeKPfVtaD0yCiUvQQiPQq2oxDtvvQy536WhoICErRL/vfNO1BCeoQKffi8WHYo9l3Uy0EkK9LcBfz/De/esUYFvJyAOm1E7tgPvvDWKsVACoWgCtk5GgE0uI444arFuJT9DU5YVTp/1PBu6zu+z5Z+3IQhNHSFeXkC6FqixE683wBAHVurJf2V41KrC7ffArLlpctyqzYfxsV8qeGNmKyQI1AElrbpKITHl2NrE4bN3MOr1272v7NR5sQKcyvHICbNUgMsS4QqeKhzp57D2igGcJAT4TB5Cng3guBojonkTbM7ZfC8WB8pVzkSxPF1sR1Qf85KjleMSqLW2Y8ObU4j9hxWZuB6CEcgicmJxyZiWsYxlLD4sE+AyqLyKQn0aPiu7eR56+VNgF4ZixZc0hc1CWIkThBhiD1FZ4/GgdxOuQQjqoAJFTEEIMcnDGJ8EHF7A7mZTrIuRAJNmO5KEVdk4QQIIIZ4Ouh9wV/U6ONztiIx6kR0KYlVTGh3xRmhhtk84z+L0Rz1fcFYe4nYj5Ody0J7ksP6DdeBaOWh5DZmDbEA3YF2D2qt5vBuLFQVAPQi0SUDb5ewl8jtRvTTrv5eho+znKN+DOPIw18fwv13P45uXO/F0gEM8ce5xvqyNw/fvEmA1cTjaK+CHF9u+cJ5pcOkIB5kUr0VCgGeQ5OiJdnl3FQ6ledzlCeJYdRrCkAVqB7uHtaxuR5shgrf8lFRauWkHHD6rFaFU6rwGOxfys39Xq1DPZ1LNf8MZvhSCUQQZD3z/wwJEHhg+wuOP1QIu2ajgmopDiN7lwoNf2QLVpNAm5nBZYM0ylrGMZUyHZQJchuCnT0DMi/C42QPn0LFzq0WLClMlClMa4MorwMZ+FfyAin+w3AlHXSW4ijB1RjDtddMIWY2XESUdYa272Yf6z06ym1pUICEcRQI8nf63iMGOUoVMsBBnAS9yvTbsvOMgPvL1/fhogoQhCNidegz5rgJ+2+pBd3sGD5W5PJAGvGqnE0Ox2Hl191+oz26xaHhmvZ76pACB/fw5TUJFHNztRi0fx7+broYWBCJH+nEGedTAAR9xlrUClaZx7BvQIE/zHaTuaBBF5GWZFMQXhJfy2fLP54wWaO5KIJcCgoOArwYwWVnzl26TVg6vqGG1GYhzWfR5hjGck7C2jkNoKAEjPVVciEwxCrl+PYf/+qAAk8Th2VMaPv8LC1K5V7ZRrJgGF1MFCOTys82jAuyqwKGMCEtcQeWlIwj+StfGA9i0thvCCHCmJz3jeZZ5Ce4VF/KzA6qKhhqNhpuc7pl+UJqOi2ir5tCWzOP+cDUMXgHPqDbcsDKC37yhGldXPgWF45GILS4d/zKWsYzFh2UCXAbBCPz/9u4DvsbrjQP4747sPUWC2EHsmK0qVR1GdaJVNatatYq2FFVVXdpSqqqoWVsHVdUq/kqEhIgI2ZG997zz/znnvffmBolENXc9388nn5vc+66T9+bmec/7nOeIJHI4ugq3QcOv31Jo1djc2kNbS48tG0SllAFeJ2T4s1t7vOyUAElbKRQ5MtheFPLmSiUlwn3FgF7CSqwChLHK1kt5uFP+rxbLF2UXBe4+KHbU3NpOcYRcBbRws4dSMzVsN1Eh/mDVLERqFBbKodTL62ZBJhsoyJ7Tf74+7ue6EaVqXvVDKgKulrK6xcKo+TsJVTohUJKNpn2ykP4/X0jP2+Ck9CK6i3wxCJ0A7xIMKryAV3bL/tOSXv+m4keKc1Moxj4DFKYDu7fzih5wbAOcXg3EXrpjAJzRS4WbLjaI8vBBllyKwDZ2SAgvRamVcJ4riqqDwKd6ifD1JAmsJCIcC1dh9g+Al6PhK2Joe4ALbKSw0/SM1jYrIUoKhEGvtg64bOMDSXEKBgxMwaFfWvIBcCqPSjg5yxEfy/JlDTOrX0P8nC/CzKZq7Mqp/TywgXAsAFa5iTAqLh+/e3ghvNQOEPmgINAHSnEVCisc7qnaIiHEshjpCBjDcZOr+Dz0eSU2uulyjVZFiVAuSpsaUEtFBlYJIkbTmTsw/zIreAZFS+HaR1whPKax/F8WBGrziWPCYLT0p2GuKwBmFzVX/+GPNwIC+WAbNiFGZr4tgnyFvGcH90rYVipx1dm2eqY3I1SlFiFKE8PUmAHuDs4VCf/9+zRPgchewes+D/ZsAR+xkAVq41OO5GLNbANGSlSi6YXXlvezc6p1EByTpxDh2ywxLxcnUqtRqpSgbVtnNLNWo8xKM5gsT1j32T4ifDNZCH4Phqjw2kYlZEaSMqoNgOVWYhRpA/faAmD2e9L0Ame6t0RBvhoeTnJYdxHuXNn6C58NsQXCQEBjd75UBIcQCTZk1f5vSVsJQuEqxtDycgRIK3hqR3CZDdw0Jf8KykyjvYQQw6IAWA+bOchPLARA19NNpHNc2+tbmFPnZBRR5ULQ1N5G+Kfo5FQGa0l1sJegLgHaBwEiMZAef8fBQkaDDXpjgRBrc27dlSrEV05BpJAh3L8nxJ5CraWUWDd0ZHWvWADsWYl8GynyXax5j2sSm1rMSP1awCYDAX7JrzsA3p9UgFKxDTpl5qDZECFPNDDFH55yIYh0bFqOyILap642Cqx3U1tr2saeT2tdVwDMvJsswbliKzSpFN7XrnblaOHtjjJrTSCZkw9bK+CD0RKIxSLs+J8Ss7cqDVbz907kMjWqWBIsC27FwnmuYDkvtRBlJvJHVcc+iNDMljb85RtIbpeGQc8KOfCXMwzfs32/sFrAjMJNBKWrCIO8yiCBGraqHHRBCH+toIj+rRFC7o4+KfTs31WJUTZCz9PZ68Z/y7BGAFxL/q9+HrBCJIajp1A+6NnMi2jlVj3uOktUqpf+YMS9vwzLTd68GNi2TBisVwdRZRkcY8Nw3cEPdt5C8J8T74ImciEocnEuw1VPYbx5eoqs9tvNRmB5igg+oWKcLq47oCkuLsYOt14QKYEuXW7yyibSIht4Zgt1jz2aliIs/05j7I0Hu2jR3d1wbwLYaI73tpngaqaNzMlwhmOukNqRJxehd6APSjU9wBUlcp764O4oQmqeGu/tURnlrXJtLzAjk6l4oZPaSC6f5Kkx6jbdcbHCBaIqNTzdqhDvFIkWfmVgV0zBCSbyWVYPuh5gFxHyWkjhZqWEh6b2uZtI+DwrsIApkAkh/x4FwHratPKH0kv4lZyNNt5pQ2tIidY8xtS5GKsEkejuB7nUGk6VZbgi9cUh++pe7mxbJeCvqRMaY8T5v1psutw6giF9zpH/g0xsBWtPoTh+caIzqnKFHmAf+2Jc9RJ6QxO087EaKTYqPl9Rv968DQqhVFi73Aq4DanZS+7nVowoPvOWkdPehWCTnjAsEqyq+xyVqcX4OVYIgDJlVhhudR1leqkEUwYL3289reI1vY2RfgB8twsyUWE2HBKv8O8v+T8AabEQIA4LEi4YJKVqXM/WTC1tBm7mABVsqnapCMXthXMZcb4Y5YrqCV8KcmgSDELI3VEArKdvKyeo7ES8UzHyzvXyjc/VM8CGBcD53+pc7FghcNq1Ff/+fKEUo7ouwNGOnVABOdJFRSgP6AJINDNl3aU32dRYF2RClHQNVU2E2qhVKQ4oSBdyYB1sy5DgIvzzTLh1OioTdiMrD3+7BsIuVYm+jyZD6SSkBajsFGgmLkdUqQn0kmnTILQBcB3pD/ri0rQBsBRV7mJdDnCAtwqdW4h4ALXnrJFGv3q1gO+W/6vlEv43f7zc8TFINAHwo52EbchKpaitipopYilAMZpUD2cHQKZQ43i4CufjhVngmIIMIx+8TAgxCiaS6No4gvwlOJnxIBRVwLhRtf/jEYtEsJVaoVIhh6qB91D/u3UD7rp+gbcPP+F/RWUAzYDSjt2w9uQe8IJV7d80/uoP/4Ik9DjSBzSBi60S4koJCtOFAWF5LkqwUY/ZGTKU6AUepk6cGoN1Qc/hkWvX0LyyAqLBmcCvzaH0rYBVmRQFJWWm0wOsLXlXVr8e/7xsOdRqNcpUEqS5WUOtEnq7X+4vvH7ogtqoB7hqZ4OrcxY4PTZ5qRAlRiK1ZSCqCoVgv4mrsI38EnZxZ149otHpQDfNNdHZaIAV9ygOK4Rn+76ogAPkhQcMfYiEEBNAAbAeNxsF0sqb8+87VpfSNCs5ucXIunYFGKIAXL1Q5u4m1FVt3dmsA2BRwlXc6BeIoGZJsI4TBlSJJCokNhGCo3gjT39osPxMHHVoh5s2HvBIL0Lg4FSE2Kng0qIE6RVsdjUjHuSopa0E4SX8TaKifj3ACgVQXqiAg5sVrto7AKxsXJUKw3sI5/qHk8Z9oVOzB7h+xyoJ+Q2KVp2RpGgCf1RXg0kuqk4NMLeBcMzRS8L36rREnC6fKaTIVG034NERQkwFBcB62jsmoLldJs6FKrHvWt2zGLnZ26OgvPyeZkAyxLqMRCRGeVElRHIZkBoD+HcCWnUWcmml1kLqg2Z2KXMjghphUUnowQYGaQJgJ48KxHrYml36A8NCPausm9jgNxTLU/ciqEs5CnpnoYN9JW5c6QDI0mD0ijUBsJWmrFU9c76Z1FQZAtyskC4XPuJsoIJUIkJwjArXjbzp+jnA9UmBYETJN3j1livS1jUC4OvZ5pflFp2mGQinBP6M0DwprwI2vlNnJRxCCNFHAbCeph45fHDFJxdkCEuqfZCQoSYKuF+TDHCJ14QAuGUgoN2Wmfb+auVEXITtky10P0vdKqEUi1CQJ0d+rgnkxDaQbWYCNvcagiUJB2BfpcIID6EH9UAlm/rayCt96PcAazUgAM5IlyGgiwNSq4S8by97IZDcctJ4c3/v1ANcnxQIhn9aBR/BmYd74imc1z0fmmwig3kb4HysGn9HqpGQaYuicr0LV23VEEIIqQfz6x74N6QiiGRqnDbPTtCakiKFRxYEt+1mEQEw6yUSuVVALRJ6kCpdheAgQTtLiJmxzUhAvpUT9nj1hXWqEFSJy9UIVwmTgJhMD7BWWf1SIJjsDM2gP81Uz87WKqTlq/HHFSOse1ZHDnB9e4C5mEsIlrtCXKFpo0qNf+Lqf9FgKliZ5ynfqrH1pPmldxBCGg8FwLdQZqtQyqeZNXOZSUKPia29MNkAG3CUIRTVN2flpeVQegmDgvI9hUAj3szSH7Ss89J4zeT1LYbBNkkIpKxyVIhSGncN4NuqQNxDD3ButgxqVjJAw16sxnYjLn2mj/X6KuTqBuUAC9RIDAuGukTz+VUqQka5cc5sSAghhkYBsB7nMzKkXrKQHDJWRSIpqvpn3vtr/L1j/1ZGViXKB2dB0b4YZZ2LUVWqRFa6+d0mZkRqFUTp8Qh3aonQVGe4Ha1CVagt8ipNJN2DTYahH/TWswyatmRwZXF18GcNJXb9YwLRr0ZhgXCOGlyZ5Fow8suFEn/lJSz9wwIu5gkh5B5QAKwnK0qF0OvmHwTelgZhCekPGnE5Csg6FaNw3E2o7ZWIMbfqD3coh8Z86dYf1jlqnLdp36BA0qjygBvQA8ykp1UHwPFpKqMufXarv47k48Rv+cjJbGAPrkqJG8nCx3pyppD/TAgh5D4HwG9Oeh7p4YfxwYKpuudsrK2wcuF0RJ7ahdhz+/D9qoXwdNcMvNLw8/HC9rVLER98ABF/78CSuZMgkdQ8lP69OuOP3auReOEQzv76HUY/NeS2/U8cMwwhRzchIeQgjuxYhe6d29V4vT7Hoq/tZQlmJlpQj0l8hDB6uiBbqAphAa5l1uz9NNf0By1Raix//KXNMDzk8gymBbzaoFxao0qDaGDgnpxS3bN/NtJEer01WOAbdeXepjCevj8Pv/+gxrSd5jMDHCGEGE0A3C2wHV5+/glci66ZN7ps/lQMHdgHry34FM9OWYgmXu7Y/OXC6h2KxTz4tbaS4qmJCzB7yWqMHjkEC94Yp1umuW8T7Fj7Ps5ejMDQMbOwadevWLV0Jh7u30O3zFOPDcD786biy+924/EX5yAqJhE/rl8ODzeXeh/LnVlQAMx617YsAXauEFIiLEBRsQpibW5olQppN81rkoBbiTLihXwAZ3cEt3gQedZOptUDrJ0M4x56gNnkJlpxaaaT/vBv5cpFmBqiQLwpTHdNCCGmFADb29li3cp5WLB8LYpKqkvPODna48VnhmLZF5t48Hr1ejzeen8NenfvhJ5dhJnKWBDbvnVzvLnoSx48nzwbhs/W78TE0cNhJRWqsr3ywhNITsvC8i+3IC4xFT/s/Q2//XUW014epdvXtPFP48dDf2DvLycQm5CCd1asR0VlFV58emi9j4UIEyag1HJ6ilicX1kk9AbGx1XgHsopmxRe8znrpvCDR1Ph0RRTIFgQX9WwHlE2I5xSqan4YU7zARNCCDFMHeCVi6bjxJlQnAm5gtmvjtE937VjW1hbWfHnteKSUpGano2gbh1w6Wo0enXtgBtxN5GbXx10nTp3GZ8unoGANi0QGZ2AoK4dcCYkvMY+TwVfwgfzX+Xfs0CZ7WvdluopL9nUp2ydoK4B9T6WW0lEIkjEd78msJJIajw2hKHWNeS+je24E1Lk6OBmhRuRlbw2cmPuuzHWvXV9RWosVL5tdK9JK8sgrmO7xnLcjLK0EDx0LS+5p3MVGVYGLx8rFOWp6lzf2N6jjbGuIfdtqsdtyH3TcdNx/9frGvq472V+g0YNgEc9/hC6dGiDYePeuu01b083VMnkKC6pOdokJ78Q3h5C7q2Xpyty8mr2OGqDYS9PNyBaeLx1Gfazs5MDbG2s4eLsCKlUgpy8mmWScvMK0bZls3ofy62cbG35TGv15e0kzCh2Lwy1riH3bSzHnXgRyLheCXWhPfxc7c3+d1ZWkKY3NxjQVApItROiGPm5rpKVIJ3l85fmw7cex3zrvlMuAylQoalTw9e9F6b8PjG1dS1133TcprOuIfdtisedmKeX8mZsAbBvE08sf/tVjJ2+lAeX5qakshLlMlm9rlTYCc4uKYG8gVcshlrXkPs2yuPONeC+/+N1b11fFhMOPF79WmZmGkQspcDIj5uvX1gI6cHVUOWkIq247lQdozpuE1jXkPs21eM25L7puOm4/+t1DX3cja1BAXDXTm3h5eHGqzPoNiCVoF/PQEwaMwIvvbGUV15gPbX6Pa9e7q7I1vTo5uQWokfn9jW2q63MkJNboHv0uqWXlv3MtllZJYOyoBgKhZIfS43teLjqtpGdW3DXY7mVUq2GsgEnjZ3ge+2yN9S6hty3qR63Ifd9P45bXloE5KYBnn5AZRnksiqTOG7d+jGXGm3flvw+oeM2jX3TcZvOuobct6ket9EOgmP5tIOfm8ErM2i/wq/F4tDR0/z7K1FxkMnlGNBHM7UugDb+fmjm642wKzf4z6ERN9ChrX+Nag0D+3fnQWpMQjL/OSziRo1t8GX69eDPM3KFAhHX4zCgT1fd6yKRiK8TFiHk9rLX73YshFiMlOh7qqRACCGEmKMG9QCXlVcgOl4IUrXKKypRUFSse373T39i2bwpKCwqQUlZOT569zWEXrmuG3R2OvgyYhJSsPajt7Bi9Q+8F/edGS9j677fIJMLt2W37z+GSWNHYPGcidjz8194sE9XjBw6AONnfqDb78YdP2P1h3N50H05MgavjhvFq1Ps+eUv/npJafldj4UQi5EcDfR4BCjWm1iCEEIIsVD3VAWiLstWbeIVGb7/YiFPQTh17hIWrvxW97pKpcIrs5bjk/fewOFtq3gAvf/w3/h8/S7dMinpWTzY/WD+VEx56SlkZOVi/vK1PHjW+vX4P7wXecHr4/iguWvRCRj3xvs1qkvc7VgIsRg3LgAuHkDCVUMfCSGEEGL6AfDzUxfV+JkNjlv08Qb+VZu0jByMf7O6N/dOgkMj8djYOXUuw+oDs6/a1OdYCLEIKiUQfMTQR0EIIYSY/lTIhBBCCCGEmBoKgAkhhBBCiEWhAJgQQgghhFgUCoAJIYQQQohFoQCYEEIIIYRYFAqACSGEEEKIRaEAmBBCCCGEWBQKgAkhhBBCiEWhAJgQQgghhFgUEbyD1IY+CEIIIYQQQhoL9QATQgghhBCLQgEwIYQQQgixKBQAE0IIIYQQi0IBMCGEEEIIsSgUABNCCCGEEIsiNfQBkIbp2zMQb0x4Fl06toGPtwcmz/0Ix06e173u6e6K9+ZMxMP9usPFyRHnL0Vi8affITE5Q7eMl4crlsydjIH9usPRwQ7xSWlYs2kfjp44p1tm1tTRePShXghs3xoyhRwdH3oR5tzmZr7emPvqGDzYpxtfNisnH4eOnsKa7/dBrlCYZZuZrasXIzCgNTzcXVBUXIozIVfw0ZqtvP2G0Fjt1rK2kuK3nV/w38HQMbNwLToR5trmkKOb0Ny3SY19r1yzDet+OABzP9dDHuqFudPGomO7lqiSyXE+LJLvzxzb3L9XZxzc9PEd9//kuLdw5VoszPE8t27hiyVzJ6F3906wspLiemwSPvtmJ86FXoUhNFa7u3Rog/fmTEC3wHZQKlX8tWWrNqO8otIk2+zfzAdL35qMPt07wdraCifPXcLiT75Dbn6hbhlXZ0esePc1DB3YByq1Ckf/Oocln33f4DZTD7CJsbezxbWYRCz6eMMdX9/y1Xvw92uCSXM/wmNjZyM1Iwd7N6yAna2NbpmvV7yFNi39MHHOh3jk+Tf5H8x3n72NzgGtawQGh/88i237j8IS2ty2ZTOIxWK8s+IbDH5uBpat2oTxzz+BhTNfgTmf57OhV/Ha25/ioaen49X5H6Nlcx98v+pdGEpjtVtr8dxJyDRQsG+INrOAoNuQ8bqvzbsPw9zbPWzIA3y5vb/8haGjZ2HUxLfx0++nYa5tDg2/UeMcs69dh/7AzdTMRg9+G/M8b1u7FBKpBC9Mew9PvDQHUTGJ2L52KQ8iDaEx2t3Eyx17vvuQB5AjXp6PcTOWIaBNC6xePgem2GY7Wxvs/nY51Go1P4/sb5XFItu+XgKRSKTbzrqV83k7x05fggkzP0TfoM74fOmbDT5eCoBNzMmzYfyfmP5Vlf4VcK9uHfDuym/5B138zTS8+9F62Npa45knH9Ytx5bZsvsIwiNjkZyWxa8oi0rK0LVTW90yq779Ed/v/AU34m7CEtp86twlzH1/DU4HX+avHz99ARu2/4Qnh/SHOZ9ndo4vXY1GWkYOQq/cwLotB9CzSwCkUgnMud3M4AeD8HC/Hlj+5RYYUmO2ubS8Ajl5hbqvisoqmHO7JRIxlr/9KlZ89QN2HDiGhOR0xCak4PDxf2CubWZ3rPTPcUFRCR4f1JdfAJhrm91dndHG349/frGeXxYQfrRmGw/IOrT1h7m2+9GBvaFQKHjAybbBtvXOivUYMfRBtGzeFKbW5j49OqG5rzfmLF3NYw/2NXvJV+jWqS0G9OnKl2nbqhkeGRCEeR+sxeXIGFwIj+I9xKMef4hfEDQEBcBmhN0uYKqqZLrn2JWUTCZH7x6ddM+xQOepxx/itxHYVRV749jaWBvsVpGxttnJ0QGFRSWwlDaz5Z4dNoivp1AoYc7tZrfiWI/BzMVfGjQIbOxz/eak5xF5aheO71mN1yc8wwNEc243uxXr28ST3yZlbb785zbsXCf0klnK3/VjD/eFm4uTwQLgxmhzfmEx4hJT8cLIR3gvIntfszt4OXkFiIiKg7m228bKCnK5gq+rVanZJgsmTa3N1lZSsKaw57TY8iqVWteeXl07oLC4tMZ5PRMSzpfp0bl9g47JOD/9yD2JS0pFano2Fs6aABcnB1hJpZgx8Tn4+nihiaebbjl2y9tKKkHU/3Yj6cIhfLp4Bqa8tRJJKdV5OJbeZnb1PHnsCOw4eAzm3ub3Zk9AXPB+vhzbxqQ5K2CM7me72S3CHft/N8p/jv9Vmzf/eBivv/sZXnj1Pd4bOnPKaCyeMwnm3G5/Px/+OO+1l7D6+314ZdZyFJWU8hxZFlRYwmfZi88Mxangy8jIzoOxuZ9tHvPaYp4aEHtuHxJDDmHay6Mw7o1lvMfUXNv9z8UIeHm48YtZtg22rUWzJvDXvPW2YyptDrsazfN4WZ4wu5BhXywfmN2R9PYUene9PN2Qp5cPzLDc58Likga3mQJgM8J67abMW4k2/r64fmYP4s8fwAO9u+DEP6H86kjr7TfGwdnJAaOnvYcnx83Fxp0/Y8NnbxvsVpGxtdnH2x27vlmGI3+exY+HjsPc2/zttp/w2JjZPJ9KpVJhzYq5MEb3q91TXhzJB5Ss3WKYwV+GOtcbd/6C4NBIfouYBcDLv9jML/JYr4u5tpvl9TNrNgsDh65ej8fcpat5z9OIoQNg7p9lTb09MKh/D+z+6U8Yo/vZ5pULpyO3oAjPTH4Xw1+eh2OnQrD16yVGFwjez3bHxCfzdIHXxj/DtxF+YgdS0rOQnVsAtd52TKXN+QXFPOhng9vYhUz0P3vh7OTIOyrY/6b7zfg++ci/wj7gh46ZDSdHez4Slr2hjuxYpevpYiMsJ784EoOem8H/eJiomCT07RGIiWOG85wcS24zyyHa//1KfutpwYfrYAltZrcP2Zc2PzLs+FYEdQ1AWEQ0zLHdD/bpytvHelT0/b7rKxz6/RTmLFkNS/ibvhQZw7fHKkOwfDxjcz/ara1mEhufotuuTK7AzbRM+DX1grG53+d6zKhHeQ7w8dMhMFb3o80sP5Tlw3Yc+CJKyyqE7a78lldPGD1yiMEqnTTGuWYDOtkXS+tivafs4o71frP3uKm1mWHjcB4YOY3ndSuUShSXlCH8r+1I1rQnJ7cAHu41BzaylBdXZyce+DcE9QCbqZLScv7matWiKU8g/+OU8AGoHW1569WUUqWCWFw9ytIS28x6fg9sWomrUXF8QJx+XpWlnGdtj5k2X8sc273k0414dPQsXvaMfY2f+QF/fvo7n+HTtTtgKec6MKAVlEpljfJC5tbuiOtxPCeSjaTXYrdT2UCb1IxsmPu5ZgHwgcMnjTKn/362uXqZmp/ZapUKIiP/v3a/zjX7O2YBMMsTZqX+/nc+HKbWZn2sU4YFvw/27gpPdxccP3WBPx8acYOnL7H8fq0Bfbrx3wkbFNcQ1ANsYtioVvam0Wru14T/IyssKkVaZg4f/ZlXUMRH9bOal2wE9LGTIfyqSpuHw3r6Pls8A8u/2oKCwhI8Mbgfv1Jm+XFafj5ecHVx5I8SsZjvg2Gjaxu7vmBjtFkIfj9GWno2X8bDzVm3PzaSurE1RpvZgIHuge34KFo2qKBls6Z4e8Y4JCanI+zKjUZvc2O1m21HX5nm/XwzNcMgeZKN0WbW492jSwDOXYzgPWRB3Trgg/lTcfDoKYPlSDZGu1lbdxz4HfNefwnpWbk8B/H1Cc/y144YoBJEY31+M6xXlPUi/viTYdO4GqPN7G5VUXEZ1nw4F19t3I3KShnGPfc439eJMxfNtt3MpDHD+R3LsvIKDOzfHUvmTMbKr7fx4NHU2syMGTUEsQmpfLmgrh34Mix9S3uXig12/PufMKxaOhPvfPQNzyVmNYF/+eNMg+vXi+AdZPzdXESntiLne389wXPbWH4jS4j39HBFdk4B9h/5G6s37q0xmQN7gy6aNRF9enSEg70dD2pZya+Dv53ULfPV8jkY89SQ2/bz3NSFPI/Q3No8+qkhtdZO9O0+Eo2tMdrM8sjYh0un9q34Bxe7fcTK2KzZtBeZ2flm/f7WxyZBuXB0s8EmwmiMNrNi+SsXTeclhKytrJCSloUDv53Exh0/85QAcz7XrMd30cwJeG7EINja2OByZDSWfr5Jd1vZXN/f33w8H82aemHUxHdgSI3VZlYa7N03x/NHFhRFxyfjq417+GeaObebBf1sohf2OgsO6/qsM4U2L5o1gf8/Zh1wKenZfLAyC4D1sR7gjxZOx9CBvXmvP8vvX/zpxgZ3zlEATAghhBBCLArlABNCCCGEEItCATAhhBBCCLEoFAATQgghhBCLQgEwIYQQQgixKBQAE0IIIYQQi0IBMCGEEEIIsSgUABNCCCGEEItCATAhhBBCCLEoFAATQogRmzf9RaSHHzb0YRBCiFmhAJgQQszQhNHD+JSihBBCbkcBMCGEmCEKgAkhpHYUABNCCCGEEIsiNfQBEEIIEfTp3gnLFkxFh7b+yMzOw/qth25bZsyoIXhu+GC+jJOjA26mZGDLniPYvv933TIhRzehuW8T/r02f/hc6FU8P3UR/97ZyYHnFg8f8gA83F2RnpmDHw8dx/pth6BWqxutvYQQYigUABNCiBFgAe3ub5cjr6AIX27YDYlEjPmvv4ScvMIay73ywjDExCfj+OkLUCqUGPpwH3zy3hsQi0XYuvcoX+b9zzdhxTvTUFZeiTWb9vHncvOF7djZ2uDgpo/R1NsDOw4eQ1pGDnp174CFs16Bt5cbX5cQQsydCN5BdLlPCCEGtvnLRRj0QE8MfPp1pGXm8OfatmqGv/evg1QqgW/3kfw5WxtrVFbJaqy765tlaNXCFw+MnKZ77u8D65BfWKzr9dWaPXU03pz8PB4bOxuJyRm65xfOfAWvT3gW/YZPRXpW7n/cWkIIMSzKASaEEAMTi8UY1L8n/jh5Xhf8MnGJqTgVfKnGsvrBr5OjPdxdnREcFomWzZvyn+9mxNABCLkUhaLiMr6u9utMSDgPtPsGBd7n1hFCiPGhFAhCCDEwDzdn2NnZ1OiR1YpPSsOjD/XW/dy7e0fMn/4Sgrp1gL2dbY1lnR0dUFJaXue+WrfwRWBAK0Se2nXH1z3dXe+5HYQQYiooACaEEBPh38wHe79bgfikVCxbtRnpWTmQyxV4ZEAvvDb+aYjEortugy1zOvgy1m89eMfXE26m/wdHTgghxoUCYEIIMbC8gmJUVFShVYumt73WpqWf7ns24I3lAE+cvaJGqsQDvbvetl5t1RxupmbCwd4WZ0Ku3LfjJ4QQU0M5wIQQYmAqlYrn+j4+uB/8fLx0z7NBcCw3WLecUiV8o9fRy/J+x9xhwovyikq4ODnc9vzh42fQq1tHPNy/x22vsfJorPoEIYSYO6oCQQghRqBju5Y4smMV8vKLsG3fUUikEkweO4KXQWM5u6wKRBt/P/y1fy1Pgdh58Bgc7Ozw0rOP8WA3MKA1+gybgtT0bL69lQun45UXnsTn63chKSUDuflFOHsxgpdB+2nLJ3x/+w6fQERUHM8l7tCuJUY8+gD6DpvKq0cQQog5owCYEEKMRN+egVg2bwoPRjOycvlEGE283DBv+ku6MmhDB/bG2zPGo7W/Lw+Ot+8/ymsHf/XBnBoBMBvM9sWyWejXM5D3EutPhMEC3llTX+AVIViPc2lpORKS03D0RDA27z4MhUJp0N8DIYT81ygAJoQQQgghFoWSvQghhBBCiEWhAJgQQgghhFgUCoAJIYQQQohFoQCYEEIIIYRYFAqACSGEEEKIRaEAmBBCCCGEWBQKgAkhhBBCiEWhAJgQQgghhFgUCoAJIYQQQohFoQCYEEIIIYRYFAqACSGEEEKIRaEAmBBCCCGEwJL8HwjmNlgLYtoPAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 700x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot predictions\n",
    "# ==============================================================================\n",
    "fig, ax = plt.subplots(figsize=(7, 3))\n",
    "data['y'].loc[data_test.index].plot(ax=ax, label='y')\n",
    "pred_sarimax['pred'].plot(ax=ax, label='pred_sarimax')\n",
    "pred_arima['pred'].plot(ax=ax, label='pred_arima')\n",
    "pred_arar['pred'].plot(ax=ax, label='pred_arar')\n",
    "pred_ets['pred'].plot(ax=ax, label='pred_ets')\n",
    "predictions_ridge['pred'].plot(ax=ax, label='pred_ridge')\n",
    "ax.set_title('Monthly fuel consumption in Spain - Predictions')\n",
    "ax.legend();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Web traffic dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Data downloading\n",
    "# ==============================================================================\n",
    "data = fetch_dataset(name=\"website_visits\", raw=True, verbose=False)\n",
    "data['date'] = pd.to_datetime(data['date'], format='%d/%m/%y')\n",
    "data = data.set_index('date')\n",
    "data = data.asfreq('1D')\n",
    "data = data.sort_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>month_1</th>\n",
       "      <th>month_2</th>\n",
       "      <th>month_3</th>\n",
       "      <th>month_4</th>\n",
       "      <th>month_5</th>\n",
       "      <th>month_6</th>\n",
       "      <th>month_7</th>\n",
       "      <th>month_8</th>\n",
       "      <th>month_9</th>\n",
       "      <th>month_10</th>\n",
       "      <th>...</th>\n",
       "      <th>month_day_23</th>\n",
       "      <th>month_day_24</th>\n",
       "      <th>month_day_25</th>\n",
       "      <th>month_day_26</th>\n",
       "      <th>month_day_27</th>\n",
       "      <th>month_day_28</th>\n",
       "      <th>month_day_29</th>\n",
       "      <th>month_day_30</th>\n",
       "      <th>month_day_31</th>\n",
       "      <th>users</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-07-01</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2324</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-02</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2201</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-03</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2146</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 51 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            month_1  month_2  month_3  month_4  month_5  month_6  month_7  \\\n",
       "date                                                                        \n",
       "2020-07-01      0.0      0.0      0.0      0.0      0.0      0.0      1.0   \n",
       "2020-07-02      0.0      0.0      0.0      0.0      0.0      0.0      1.0   \n",
       "2020-07-03      0.0      0.0      0.0      0.0      0.0      0.0      1.0   \n",
       "\n",
       "            month_8  month_9  month_10  ...  month_day_23  month_day_24  \\\n",
       "date                                    ...                               \n",
       "2020-07-01      0.0      0.0       0.0  ...           0.0           0.0   \n",
       "2020-07-02      0.0      0.0       0.0  ...           0.0           0.0   \n",
       "2020-07-03      0.0      0.0       0.0  ...           0.0           0.0   \n",
       "\n",
       "            month_day_25  month_day_26  month_day_27  month_day_28  \\\n",
       "date                                                                 \n",
       "2020-07-01           0.0           0.0           0.0           0.0   \n",
       "2020-07-02           0.0           0.0           0.0           0.0   \n",
       "2020-07-03           0.0           0.0           0.0           0.0   \n",
       "\n",
       "            month_day_29  month_day_30  month_day_31  users  \n",
       "date                                                         \n",
       "2020-07-01           0.0           0.0           0.0   2324  \n",
       "2020-07-02           0.0           0.0           0.0   2201  \n",
       "2020-07-03           0.0           0.0           0.0   2146  \n",
       "\n",
       "[3 rows x 51 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Features based on calendar\n",
    "# ==============================================================================\n",
    "data['month'] = data.index.month\n",
    "data['month_day'] = data.index.day\n",
    "data['week_day'] = data.index.day_of_week\n",
    "\n",
    "# One hot encoding transformer\n",
    "# ==============================================================================\n",
    "one_hot_encoder = make_column_transformer(\n",
    "    (\n",
    "        OneHotEncoder(sparse_output=False, drop='if_binary'),\n",
    "        ['month', 'week_day', 'month_day'],\n",
    "    ),\n",
    "    remainder=\"passthrough\",\n",
    "    verbose_feature_names_out=False,\n",
    ").set_output(transform=\"pandas\")\n",
    "\n",
    "data = one_hot_encoder.fit_transform(data)\n",
    "data.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training dates   : 2020-07-01 00:00:00 --- 2021-03-30 00:00:00  (n=273)\n",
      "Test dates       : 2021-03-31 00:00:00 --- 2021-08-25 00:00:00  (n=148)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 700x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Split data train-val-test\n",
    "# ==============================================================================\n",
    "end_train = '2021-03-30 23:59:00'\n",
    "data_train = data.loc[: end_train, :]\n",
    "data_test  = data.loc[end_train:, :]\n",
    "exog_features = [col for col in data.columns if col.startswith(('month_', 'week_day_', 'month_day_'))]\n",
    "print(f\"Training dates   : {data_train.index.min()} --- {data_train.index.max()}  (n={len(data_train)})\")\n",
    "print(f\"Test dates       : {data_test.index.min()} --- {data_test.index.max()}  (n={len(data_test)})\")\n",
    "\n",
    "# Plot\n",
    "# ======================================================================================\n",
    "fig, ax = plt.subplots(figsize=(7, 3))\n",
    "data_train['users'].plot(ax=ax, label='train')\n",
    "data_test['users'].plot(ax=ax, label='test')\n",
    "ax.set_title('Daily web visits')\n",
    "ax.legend();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "b0ad7cab4ace4af59d009d12495e490c",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/22 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Backtesting ForecasterStats with ARAR skforecast\n",
    "# ==============================================================================\n",
    "cv = TimeSeriesFold(\n",
    "        steps              = 7,\n",
    "        initial_train_size = len(data.loc[:end_train]),\n",
    "        refit              = True,\n",
    "        fixed_train_size   = False,\n",
    "      )\n",
    "forecaster = ForecasterStats(\n",
    "                 estimator=Arar(max_ar_depth=10, max_lag=10)\n",
    "             )\n",
    "\n",
    "start = timeit.default_timer()\n",
    "metric_arar, pred_arar = backtesting_stats(\n",
    "    forecaster = forecaster,\n",
    "    y          = data['users'],\n",
    "    cv         = cv,\n",
    "    metric     = 'mean_absolute_error'\n",
    ")\n",
    "stop = timeit.default_timer()\n",
    "elapsed_time_arar = stop - start"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "959b30bc451749f7a18b65edd1521bd8",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/22 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Backtesting ForecasterStats with sklearn Ridge\n",
    "# ==============================================================================\n",
    "params = {'alpha': np.float64(2.154434690031882)}\n",
    "forecaster = ForecasterRecursive(\n",
    "                 estimator     = Ridge(**params, random_state=123),\n",
    "                 lags          = 14,\n",
    "                 transformer_y = StandardScaler(),\n",
    "                 forecaster_id = 'web_traffic'\n",
    "             )\n",
    "\n",
    "start = timeit.default_timer()\n",
    "metric_ridge, predictions_ridge = backtesting_forecaster(\n",
    "    forecaster = forecaster,\n",
    "    y          = data['users'],\n",
    "    exog       = data[exog_features],\n",
    "    cv         = cv,\n",
    "    metric     = 'mean_absolute_error'\n",
    ")\n",
    "stop = timeit.default_timer()\n",
    "elapsed_time_ridge = stop - start"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "db1c4804816f467d90be3d5997d1aa34",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/22 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Backtesting ForecasterStats with sarimax statsmodels\n",
    "# ==============================================================================\n",
    "forecaster = ForecasterStats(\n",
    "                 estimator=Sarimax(order=(2, 1, 1), seasonal_order=(1, 1, 1, 7), maxiter=500),\n",
    "             )\n",
    "\n",
    "start = timeit.default_timer()\n",
    "metric_sarimax, pred_sarimax = backtesting_stats(\n",
    "    forecaster = forecaster,\n",
    "    y          = data['users'],\n",
    "    cv         = cv,\n",
    "    metric     = 'mean_absolute_error'\n",
    ")\n",
    "stop = timeit.default_timer()\n",
    "elapsed_time_sarimax = stop - start"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Backtesting ForecasterStats with sarimax statsmodels with exogenous variables\n",
    "# ==============================================================================\n",
    "# forecaster = ForecasterStats(\n",
    "#                  estimator=Sarimax(order=(2, 1, 1), seasonal_order=(1, 1, 1, 7), maxiter=500),\n",
    "#              )\n",
    "# start = timeit.default_timer()\n",
    "# metric_sarimax_exog, pred_sarimax_exog = backtesting_stats(\n",
    "#                     forecaster = forecaster,\n",
    "#                     y          = data['users'],\n",
    "#                     exog       = data.drop(columns='users'),\n",
    "#                     cv         = cv,\n",
    "#                     metric     = 'mean_absolute_error'\n",
    "#                 )\n",
    "# stop = timeit.default_timer()\n",
    "# elapsed_time_sarimax_exog = stop - start"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Model</th>\n",
       "      <th>MAE</th>\n",
       "      <th>Elapsed Time (s)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>sklearn Ridge</td>\n",
       "      <td>180.156629</td>\n",
       "      <td>0.176973</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>SARIMAX statsmodels</td>\n",
       "      <td>217.191841</td>\n",
       "      <td>13.873680</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ARAR skforecast</td>\n",
       "      <td>238.186705</td>\n",
       "      <td>0.135392</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 Model         MAE  Elapsed Time (s)\n",
       "0        sklearn Ridge  180.156629          0.176973\n",
       "1  SARIMAX statsmodels  217.191841         13.873680\n",
       "2      ARAR skforecast  238.186705          0.135392"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "results = pd.DataFrame(\n",
    "    {\n",
    "        \"Model\": [\n",
    "            \"ARAR skforecast\",\n",
    "            \"sklearn Ridge\",\n",
    "            \"SARIMAX statsmodels\",\n",
    "            # \"SARIMAX statsmodels Exogenous\",\n",
    "        ],\n",
    "        \"MAE\": [\n",
    "            metric_arar.at[0, \"mean_absolute_error\"],\n",
    "            metric_ridge.at[0, \"mean_absolute_error\"],\n",
    "            metric_sarimax.at[0, \"mean_absolute_error\"],\n",
    "            # metric_sarimax_exog.at[0, \"mean_absolute_error\"],\n",
    "        ],\n",
    "        \"Elapsed Time (s)\": [\n",
    "            elapsed_time_arar,\n",
    "            elapsed_time_ridge,\n",
    "            elapsed_time_sarimax,\n",
    "            # elapsed_time_sarimax_exog,\n",
    "        ],\n",
    "    }\n",
    ")\n",
    "results = results.sort_values(by=\"MAE\").reset_index(drop=True)\n",
    "results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 700x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot predictions\n",
    "# ==============================================================================\n",
    "fig, ax = plt.subplots(figsize=(7, 3))\n",
    "data['users'].loc[data_test.index].plot(ax=ax, label='y')\n",
    "pred_sarimax['pred'].plot(ax=ax, label='pred_sarimax')\n",
    "pred_arar['pred'].plot(ax=ax, label='pred_arar')\n",
    "predictions_ridge['pred'].plot(ax=ax, label='pred_ridge')\n",
    "ax.set_title('Daily web visits - Predictions')\n",
    "ax.legend();"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "skforecast_py12",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.11"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
